# dsp.SpectrumAnalyzer

(To be removed) Display frequency spectrum of time-domain signals

**
**

**The**`dsp.SpectrumAnalyzer`

object will be removed in a future release. Use the`spectrumAnalyzer`

MATLAB^{®}object instead.**The**`CCDFMeasurements`

property of the`dsp.SpectrumAnalyzer`

object will be removed in a future release. Use the`powermeter`

object instead to compute and visualize CCDF measurements.

**
**

**For more information on how to replace your existing code, see Version History.**

## Description

The Spectrum Analyzer System object™ displays the frequency spectrum of time-domain signals. This scope supports variable-size input, which allows the input frame size to change. Frame size is the first dimension of the input vector. The number of input channels must remain constant.

To display the spectra of signals in the Spectrum Analyzer:

Create the

`dsp.SpectrumAnalyzer`

object and set its properties.Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects?

## Creation

### Syntax

### Description

`scope = dsp.SpectrumAnalyzer`

creates a Spectrum Analyzer
System object. This object displays the frequency spectrum of real- and complex-valued
floating- and fixed-point signals.

`scope = dsp.SpectrumAnalyzer(ports)`

creates a Spectrum Analyzer
object and sets the `NumInputPorts`

property to the value of
`ports`

.

`scope = dsp.SpectrumAnalyzer(Name,Value)`

sets properties using
one or more name-value pairs. Enclose each property name in single quotes.

## Properties

Unless otherwise indicated, properties are *nontunable*, which means you cannot change their
values after calling the object. Objects lock when you call them, and the
`release`

function unlocks them.

If a property is *tunable*, you can change its value at
any time.

For more information on changing property values, see System Design in MATLAB Using System Objects.

### Frequently Used

`NumInputPorts`

— Number of input ports

`1`

(default) | integer between [1, 96]

Number of input ports, specified as a positive integer. Each signal coming through a separate input becomes a separate channel in the scope. You must invoke the scope with the same number of inputs as the value of this property.

`InputDomain`

— Domain of input signal

`"Time"`

(default) | `"Frequency"`

The domain of the input signal you want to visualize, specified as
`"Time"`

or `"Frequency"`

. If you visualize
time-domain signals, the Spectrum Analyzer transforms the signal to the frequency
spectrum based on the algorithm specified in the `Method`

property.

#### Scope Window Use

In the **Estimation** tab on the Spectrum Analyzer toolstrip, set
**Input Domain** to `Time`

or
`Frequency`

.

**Data Types: **`char`

| `string`

`SpectrumType`

— Spectrum type

`"Power"`

(default) | `"Power density"`

| `"RMS"`

Spectrum type, specified as one of these:

`"Power"`

— Power spectrum

`"Power density"`

— Power spectral density. The power spectral
density is the magnitude squared of the spectrum normalized to a bandwidth of 1
Hz.

`"RMS"`

— Root mean square. The root mean square shows the square
root of the mean square. Use this option to view the frequency of voltage or current
signals.

**Tunable: **Yes

#### Dependency

To enable this property, set `InputDomain`

to
`"Time"`

.

#### Scope Window Use

In the **Scope** tab on the Spectrum Analyzer toolstrip, select
**Spectrum**. Click **Spectrum** to select
`Power`

, `Power Density`

, or
`RMS`

.

To enable these options, set the **Input
Domain** on the **Estimation** tab to
`Time`

.

**Data Types: **`char`

| `string`

`ViewType`

— Viewer type

`"Spectrum"`

(default) | `"Spectrogram"`

| `"Spectrum and spectrogram"`

Specify the spectrum type as one of `"Spectrum"`

,
`"Spectrogram"`

, or `"Spectrum and spectrogram"`

.

`"Spectrum"`

— Shows the power spectrum.`"Spectrogram"`

— Shows frequency content over time. Each line of the spectrogram is one periodogram. Time scrolls from the bottom to the top of the display. The most recent spectrogram update is at the bottom of the display.`"Spectrum and Spectrogram"`

— Shows a dual view of a spectrum and spectrogram.

**Tunable: **Yes

#### Scope Window Use

In the **Analyzer** tab on the Spectrum Analyzer toolstrip,
select **Spectrum**, **Spectrogram**, or
both.

**Data Types: **`char`

| `string`

`SampleRate`

— Sample rate of input

`10000`

(default) | finite scalar

Specify the sample rate, in hertz, of the input signals as a finite numeric scalar.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, set **Sample rate (Hz)**.

`Method`

— Spectrum estimation method

`"Filter Bank"`

(default) | `"Welch"`

Spectrum estimation method, specified as one of the following:

`"Filter bank"`

–– Use an analysis filter bank to estimate the power spectrum. Compared to Welch's method, this method has a lower noise floor, better frequency resolution, and lower spectral leakage and requires fewer samples per update.`"Welch"`

–– Use Welch's method of averaged modified periodograms.

For more details on these methods, see Algorithms.

**Tunable: **Yes

#### Dependency

To enable this property, set `InputDomain`

to
`"Time"`

.

#### Scope Window Use

In the **Estimation** tab of the Spectrum Analyzer toolstrip, set
**Method** to `Filter bank`

or
`Welch`

.

To enable this parameter, set **Input Domain** to
`Time`

in the **Estimation**
tab.

**Data Types: **`char`

| `string`

`PlotAsTwoSidedSpectrum`

— Option to plot a two-sided spectrum

`true`

(default) | `false`

Option to plot a two-sided spectrum, specified as one of the following:

`true`

— Compute and plot two-sided spectral estimates. When the input signal is complex valued, you must set this property to`true`

.`false`

— Compute and plot one-sided spectral estimates. If you set this property to`false`

, then the input signal must be real valued.When you set this property to

`false`

, the Spectrum Analyzer uses power-folding. The*y*-axis values are twice the amplitude that they would be if you were to set this property to`true`

, except at`0`

and the Nyquist frequency. A one-sided power spectral density (PSD) contains the total power of the signal in the frequency interval from DC to half the Nyquist rate. For more information, see`pwelch`

.

**Tunable: **Yes

#### Scope Window Use

Click the **Spectrum** tab or the
**Spectrogram** tab (if enabled) of the Spectrum Analyzer
toolstrip. In the **Trace Options** section, select
**Two-Sided Spectrum** to compute and plot two-sided spectral
estimates.

**Data Types: **`logical`

`FrequencyScale`

— Frequency scale

`"Linear"`

(default) | `"Log"`

Scale to display frequency, specified as one of the following:

`"Linear"`

— Use a linear scale to display frequencies on the*x*-axis. To use the`"Linear"`

setting, you must also set the`PlotAsTwoSidedSpectrum`

property to`true`

.`"Log"`

— Use a logarithmic scale to display frequencies on the*x*-axis. To use the`"Log"`

setting, you must also set the`PlotAsTwoSidedSpectrum`

property to`false`

.

**Tunable: **Yes

#### Scope Window Use

Click the **Spectrum** tab or the
**Spectrogram** tab (if enabled) of the Spectrum Analyzer
toolstrip. In the **Scale** section, set the **Frequency
Scale** to `Linear`

or
`Log`

.

To set the **Frequency Scale** to `Log`

,
clear the **Two-Sided Spectrum** check box in the **Trace
Options** section in the **Spectrum** or the
**Spectrogram** tab (if enabled). If you select the
**Two-Sided Spectrum** check box, then you must set the
**Frequency Scale** to
`Linear`

.

**Data Types: **`char`

| `string`

### Advanced

`FrequencySpan`

— Frequency span mode

`"Full"`

(default) | `"Span and center frequency"`

| `"Start and stop frequencies"`

Frequency span mode, specified as one of the following:

`"Full"`

–– The Spectrum Analyzer computes and plots the spectrum over the entire Nyquist Frequency Interval.`"Span and center frequency"`

–– The Spectrum Analyzer computes and plots the spectrum over the interval specified by the`Span`

and`CenterFrequency`

properties.`"Start and stop frequencies"`

–– The Spectrum Analyzer computes and plots the spectrum over the interval specified by the`StartFrequency`

and`StopFrequency`

properties.

**Tunable: **Yes

#### Dependency

To enable this property, set `InputDomain`

to
`"Time"`

.

#### Scope Window Use

Click the **Estimation** tab on the Spectrum Analyzer toolstrip.
In the **Frequency Options** section, set **Frequency
Span** to `Full`

, ```
Span and Center
Frequency
```

, or ```
Start and Stop
Frequencies
```

.

To enable the **Frequency Span**, set **Input
Domain** to `Time`

.

**Data Types: **`char`

| `string`

`Span`

— Frequency span to compute spectrum

`10e3`

(default) | real positive scalar

Specify the frequency span, in hertz, over which the Spectrum Analyzer computes
and plots the spectrum. The overall span, defined by this property and the
`CenterFrequency`

property, must fall within the Nyquist Frequency Interval.

**Tunable: **Yes

#### Dependency

To enable this property, set `FrequencySpan`

to
`"Span and center frequency"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, clear the **Full frequency span**
check box and set `Span`

.

`StartFrequency`

— Start frequency to compute spectrum

`-5e3`

(default) | real scalar

Start of the frequency interval over which spectrum is computed, specified in
hertz as a real scalar. The overall span, which is defined by this property and
`StopFrequency`

, must fall within the Nyquist Frequency Interval.

**Tunable: **Yes

#### Dependency

To enable this property, set `FrequencySpan`

to
`"Start and stop frequencies"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, clear the **Full frequency span** and
change `Span`

to `FStart`

. Set
**FStart (Hz)**.

`StopFrequency`

— Stop frequency to compute spectrum

`5e3`

(default) | real scalar

End of the frequency interval over which spectrum is computed, specified in hertz
as a real scalar. The overall span, which is defined by this property and the
`StartFrequency`

property, must fall within the Nyquist Frequency Interval.

**Tunable: **Yes

#### Dependency

To enable this property, set `FrequencySpan`

to
`"Start and stop frequencies"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, clear the **Full frequency span** and
change `Span`

to `FStart`

. Set
**FStop (Hz)**.

`CenterFrequency`

— Center of frequency span

`0`

(default) | real scalar

Specify in hertz the center frequency of the span over which the Spectrum Analyzer
computes and plots the spectrum. The overall frequency span, defined by the
`Span`

and this property, must fall within the Nyquist Frequency Interval.

**Tunable: **Yes

#### Dependency

To enable this property, set `FrequencySpan`

to
`"Span and center frequency"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the
**Main**, clear **Full frequency span** and set
**CF (Hz)**.

`FrequencyResolutionMethod`

— Frequency resolution method

`"rbw"`

(default) | `"num-frequency-bands"`

| `"window-length"`

Frequency resolution method of the spectrum analyzer, specified as one of these options:

`"rbw"`

–– The`RBWSource`

and`RBW`

properties control the frequency resolution (in Hz) of the analyzer.`"num-frequency-bands"`

–– Applies only when you set`Method`

to`"filter-bank"`

. The`FFTLengthSource`

and`FFTLength`

properties control the frequency resolution.`"window-length"`

–– Applies only when you set`Method`

to`"welch"`

. The`WindowLength`

property controls the frequency resolution.

**Tunable: **Yes

#### Dependency

To enable this property, set `InputDomain`

to
`"time"`

.

#### Scope Window Use

Click the **Estimation** tab on the Spectrum Analyzer toolstrip.
In the **Frequency Resolution** section, set **Resolution
Method** to one of the available options.

**Data Types: **`char`

| `string`

`RBWSource`

— Source of resolution bandwidth value

`"Auto"`

(default) | `"Property"`

Specify the source of the resolution bandwidth (RBW) as either
`"Auto"`

or `"Property"`

.

`"Auto"`

— The Spectrum Analyzer adjusts the spectral estimation resolution to ensure that there are 1024 RBW intervals over the defined frequency span.`"Property"`

— Specify the resolution bandwidth directly using the`RBW`

property.

**Tunable: **Yes

#### Dependency

To enable this property, set either:

`InputDomain`

to`"Time"`

and`FrequencyResolutionMethod`

to`"RBW"`

.`InputDomain`

to`"Frequency"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, set **RBW (Hz)**.

**Data Types: **`char`

| `string`

`RBW`

— Resolution bandwidth

`9.76`

(default) | real positive scalar

RBW controls the spectral resolution of Spectrum Analyzer. Specify the resolution bandwidth in hertz as a real positive scalar. You must specify a value to ensure that there are at least two RBW intervals over the specified frequency span. Thus, the ratio of the overall span to RBW must be greater than two:

$$\frac{span}{RBW}>2$$

You can specify the overall span in different ways based on how you
set the `FrequencySpan`

property.

#### Dependency

To enable, set:

`RBWSource`

to`"Property"`

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, set **RBW (Hz)**.

`WindowLength`

— Window length

`1024`

(default) | integer greater than 2

Control the frequency resolution by specifying the window length, in samples used to compute the spectral estimates. The window length must be an integer scalar greater than 2.

**Tunable: **Yes

#### Dependencies

To enable this property, set:

`FrequencyResolutionMethod`

to`"WindowLength"`

, which controls the frequency resolution based on your window length setting`Method`

to`"Welch"`

#### Scope Window Use

Open the **Spectrum Settings**. Change the **RBW
(Hz)** dropdown to `Window length`

.

`FFTLengthSource`

— Source of FFT length

`"auto"`

(default) | `"property"`

Source of the FFT length, specified as one of these:

`"auto"`

–– The value of FFT length depends on the setting of the frequency resolution method. When you set:`FrequencyResolutionMethod`

to`"rbw"`

, the FFT length equals the number of samples per update,*N*. For more details on_{samples}*N*, see the Algorithms section._{samples}`FrequencyResolutionMethod`

to`"window-length"`

, the FFT length equals the value you specify in the`WindowLength`

property or 1024, whichever is larger.`FrequencyResolutionMethod`

to`"num-frequency-bands"`

, the FFT length equals the input frame size (number of rows).

`"property"`

–– The number of FFT points equals the value you specify in the`FFTLength`

property.

**Tunable: **Yes

#### Dependency

To enable this property, set:

`Method`

to`"welch"`

.`Method`

to`"filter-bank"`

and`FrequencyResolutionMethod`

to`"num-frequency-bands"`

.

#### Scope Window Use

Click the **Estimation** tab on the spectrum analyzer toolstrip.
In the **Frequency Resolution** section, set the **FFT
Length** to `Auto`

or a positive
integer.

**Data Types: **`char`

| `string`

`FFTLength`

— Length of FFT

`1024`

(default) | positive integer

Specify the length of the FFT that the Spectrum Analyzer uses to compute spectral estimates.

If `FrequencyResolutionMethod`

is `"RBW"`

, the
FFT length is set as the window length required to achieve the specified resolution
bandwidth value or 1024, whichever is larger.

**Tunable: **Yes

#### Dependencies

To use this property, the following must be true:

`FrequencyResolutionMethod`

is set to`"WindowLength"`

or`"NumFrequencyBands"`

`FFTLength`

is greater than or equal to the`WindowLength`

.`FFTLengthSource`

is set to`"Property"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, next to the **RBW (Hz)** option,
enter a number or select `Auto`

.

`NumTapsPerBand`

— Number of filter taps per frequency band

`12`

(default) | positive even scalar

Specify the number of filter taps or coefficients for each frequency band. This
number must be a positive even integer. This value corresponds to the number of filter
coefficients per polyphase branch. The total number of filter coefficients is equal to
`NumTapsPerBand`

+ `FFTLength`

.

#### Dependency

To enable this property, set `Method`

to ```
"Filter
Bank"
```

#### Scope Window Use

Open the **Spectrum Settings**. In the **Main
options** section, set **Taps per band**.

`FrequencyVectorSource`

— Source of frequency vector

`"Auto"`

(default) | `"Property"`

`"Auto"`

— The frequency vector is calculated from the length of the input. See Frequency Vector.`"Property"`

— Enter a custom vector as the frequency vector.

#### Dependency

To enable this property, set `InputDomain`

to
`"Frequency"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Frequency
input options** section, set **Frequency (Hz)**.

**Data Types: **`char`

| `string`

`FrequencyVector`

— Custom frequency vector

`[-5000 5000]`

(default) | monotonically increasing vector

Custom frequency vector, specified as a monotonically increasing vector. This vector
determines the *x*-axis of the display. The vector must be monotonically
increasing and must have the same length as the input signal frame size.

**Tunable: **Yes

#### Dependency

To enable this property, set:

`InputDomain`

to`"Frequency"`

.`FrequencyVectorSource`

to`"Property"`

.

#### Scope Window Use

Click the **Estimation** tab on the Spectrum Analyzer toolstrip. In the
**Domain** section, set **Frequency (Hz)** to a
monotonically increasing vector of length equal to the input signal frame size.

To enable the **Frequency (Hz)**, set **Input Domain**
to `Frequency`

.

**Data Types: **`single`

| `double`

| `int8`

| `int16`

| `int32`

| `int64`

| `uint8`

| `uint16`

| `uint32`

| `uint64`

`OverlapPercent`

— Overlap percentage

`0`

(default) | real, scalar value

The percentage overlap between the previous and current buffered data segments, specified as a real, scalar value. The overlap creates a window segment that is used to compute a spectral estimate. The value must be greater than or equal to zero and less than 100.

**Tunable: **Yes

#### Scope Window Use

Open the **Spectrum Settings**. In the **Window
options** section, set **Overlap (%)**.

`Window`

— Window function

`"Hann"`

(default) | `"Rectangular"`

| `"Chebyshev"`

| `"Flat Top"`

| `"Hamming"`

| `"Kaiser"`

| `"Blackman-Harris"`

| `"Custom"`

Specify a window function for the spectral estimator. The following table shows preset windows. For more information, follow the link to the corresponding function reference in the Signal Processing Toolbox™ documentation.

Window Option | Corresponding Signal Processing Toolbox Function |
---|---|

`"Rectangular"` | `rectwin` |

`"Chebyshev"` | `chebwin` |

`"Flat Top"` | `flattopwin` |

`"Hamming"` | `hamming` |

`"Hann"` | `hann` |

`"Kaiser"` | `kaiser` |

`"Blackman-Harris"` | `blackmanharris` |

To set your own spectral estimation window, set this property to
`"Custom"`

and specify a custom window function in the `CustomWindow`

property.

**Tunable: **Yes

#### Dependency

To enable this property, set:

`InputDomain`

to`"Time"`

.`Method`

to`"Welch"`

#### Scope Window Use

Click the **Estimation** tab on the Spectrum Analyzer toolstrip.
In the **Window Options** section, set the
**Window**.

To enable the **Window**, set **Input Domain**
to `Time`

and **Method** to
`Welch`

in the **Estimation** tab on
the Spectrum Analyzer toolstrip.

**Data Types: **`char`

| `string`

`CustomWindow`

— Name of custom window function

`"hann"`

(default) | character vector | string scalar

Name of the custom window function, specified as a character vector or string scalar. The name of the custom window function must be on the MATLAB path. Use this property if you want to customize the window using additional properties available with the Signal Processing Toolbox version of the window function.

**Tunable: **Yes

#### Example

Define and use a custom window function.

function w = my_hann(L) w = hann(L, 'periodic') end scope.Window = 'Custom'; scope.CustomWindow = 'my_hann'

#### Dependency

To use this property, set `Window`

to
`"Custom"`

.

#### Scope Window Use

Click the **Estimation** tab on the Spectrum Analyzer toolstrip.
In the **Window Options** section, for the
**Window**, enter the name of the custom window
function.

**Data Types: **`char`

| `string`

`SidelobeAttenuation`

— Sidelobe attenuation of window

`60`

(default) | real positive scalar

The window sidelobe attenuation, in decibels (dB). The value must be greater than
or equal to `45`

.

**Tunable: **Yes

#### Dependency

To enable this property, set `Window`

to
`"Chebyshev"`

or `"Kaiser"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Window
options** section, set **Attenuation (dB)**.

`InputUnits`

— Units of frequency input

`"dBm"`

(default) | `"dBV"`

| `"dBW"`

| `"Vrms"`

| `"Watts"`

Select the units of the frequency-domain input. This property allows the Spectrum
Analyzer to scale frequency data if you choose a different display unit with the
`SpectrumUnits`

property.

#### Dependency

This option is only available when `InputDomain`

is set to
`Frequency`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Frequency
input options** section, set **Input units**.

**Data Types: **`char`

| `string`

`SpectrumUnits`

— Units of the spectrum

`"dBm"`

(default) | `"dBFS"`

| `"dBV"`

| `"dBW"`

| `"Vrms"`

| `"Watts"`

| `"dBm/Hz"`

| `"dBW/Hz"`

| `"dBFS/Hz"`

| `"Watts/Hz"`

| `"Auto"`

Specify the units in which the Spectrum Analyzer displays power values.

**Tunable: **Yes

#### Dependency

The spectrum units available depend on the value you specify in the
`SpectrumType`

property.

`InputDomain` | `SpectrumType` | Allowed
`SpectrumUnits` |
---|---|---|

`"Time"` | `"Power"` | `"dBm"` , `"dBW"` ,
`"dBFS"` ,
`"Watts"` |

`"Power density"` | `"dBm/Hz"` ,
`"dBW/Hz"` ,`"dBFS/Hz"` ,
`"Watts/Hz"` | |

`"RMS"` | `"dBV"` , `"Vrms"` | |

`"Frequency"` | ― | `"Auto"` ,
`"dBm"` , `"dBV"` ,
`"dBW"` , `"Vrms"` ,
`"Watts"` |

If you set the `InputDomain`

property to
`"Frequency"`

and the `SpectrumUnits`

property to `"Auto"`

, the Spectrum Analyzer assumes the spectrum
units to be equal to input units specified in the `InputUnits`

property. If you set `InputDomain`

to `"Time"`

and `SpectrumUnits`

to any option other than
`"Auto"`

, then the Spectrum Analyzer converts the units
specified in `InputUnits`

to the units specified in
`SpectrumUnits`

.

#### Scope Window Use

Click the **Spectrum** tab on the Spectrum Analyzer toolstrip. In
the **Scale** section, set **Spectrum
Unit**.

**Data Types: **`char`

| `string`

`FullScaleSource`

— Source of full scale

`"Auto"`

(default) | `"Property"`

Specify the source of the dBFS scaling factor as either `"Auto"`

or
`"Property"`

.

`"Auto"`

–– The Spectrum Analyzer adjusts the scaling factor based on the input data.`"Property"`

–– Specify the full-scale scaling factor using the`FullScale`

property.

**Tunable: **Yes

#### Dependency

To enable this property, set:

`InputDomain`

to`"Time"`

`SpectrumType`

to`"Power"`

or`"Power density"`

`SpectrumUnits`

to`"dBFS"`

or`"dBFS/Hz"`

(when spectrum type is set to`"Power density"`

)

#### Scope Window Use

Click the **Spectrum** tab on the Spectrum Analyzer toolstrip. In
the **Scale** section, set the **Full Scale** to
either `Auto`

or a positive scalar.

To enable the **Full Scale**:

In the

**Analyzer**tab, set the spectrum type to`Power`

or`Power Density`

.In the

**Estimation**tab, set**Input Domain**to`Time`

.In the

**Spectrum**tab, set**Spectrum Unit**to`dBFS`

or`dBFS/Hz`

(when spectrum type is set to`Power Density`

).

**Data Types: **`char`

| `string`

`FullScale`

— Full scale

`1`

(default) | positive scalar

Specify a real positive scalar for the `dBFS`

full scale.

**Tunable: **Yes

#### Dependency

To enable this option set:

`SpectrumUnits`

to`"dBFS"`

`FullScaleSource`

to`"Property"`

#### Scope Window Use

Open the **Spectrum Settings**. In the **Trace
options** section, set **Full scale** to
`Auto`

or enter a number.

`AveragingMethod`

— Smoothing method

`"VBW"`

(default) | `"Exponential"`

Averaging method, specified as one of the following:

`"VBW"`

— Video bandwidth method. The object uses a lowpass filter to smooth the trace and decrease noise. Use the`VBWSource`

and`VBW`

properties to specify the VBW value.`"Exponential"`

— Weighted average of samples. The object computes the average over samples weighted by an exponentially decaying forgetting factor. Use the`ForgettingFactor`

property to specify the weighted forgetting factor.

For more information, see Averaging Method.

**Tunable: **Yes

#### Dependency

To enable this property, set `InputDomain`

to
`"Time"`

.

#### Scope Window Use

Click the **Estimation** tab on the Spectrum Analyzer
toolstrip. In the **Averaging** section, set
**Averaging Method** to
`VBW`

or
`Exponential`

.

To enable the **Averaging Method**, set
**Input Domain** to
`Time`

.

**Data Types: **`char`

| `string`

`SpectralAverages`

— Number of spectral averages

`1`

(default) | positive integer

The Spectrum Analyzer computes the current power spectrum estimate by computing a
running average of the last *N* power spectrum estimates. This
property defines *N*.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrum"`

.

#### Dependency

This property applies only when the `AveragingMethod`

is
`"Running"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Trace
options** section, set **Averages**.

`ForgettingFactor`

— Weighting forgetting factor

`0.9`

(default) | scalar in the range (0,1]

Specify the exponential weighting as a scalar value greater than 0 and less than or equal to 1.

#### Dependency

This property applies only when the `AveragingMethod`

is
`"Exponential"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Trace
options** section, set **Forgetting factor**.

`ReferenceLoad`

— Reference load

`1`

(default) | real positive scalar

The load the scope uses as a reference to compute power levels.

**Tunable: **Yes

#### Scope Window Use

Open the **Spectrum Settings**. In the **Trace
options** section, set **Ref. load (Ohms)**.

`FrequencyOffset`

— Frequency offset

`0`

(default) | scalar | vector

Scalar — Apply the same frequency offset to all channels, specified in hertz as a character vector.

Vector — apply a specific frequency offset for each channel, specify a vector of frequencies. The vector length must be equal to number of input channels.

The frequency-axis values are offset by the values specified in this property. The overall span must fall within the Nyquist Frequency Interval. You can control the overall span in different ways based on how you set the

`FrequencySpan`

property.

**Tunable: **Yes

#### Scope Window Use

Open the **Spectrum Settings**. In the **Trace
options** section, set **Offset (Hz)**.

### Spectrogram

`SpectrogramChannel`

— Channel for which spectrogram is plotted

`1`

(default) | positive scalar integer

Specify the channel for which the spectrogram is plotted, as a real, positive
scalar integer in the range [1 *N*], where *N* is
the number of input channels.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrogram"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Spectrogram
options** section, select a **Channel**.

`TimeResolutionSource`

— Source of the time resolution value

`"Auto"`

(default) | `"Property"`

Specify the source for the time resolution of each spectrogram line as either
`"Auto"`

or `"Property"`

. The `TimeResolution`

property shows the time resolution for the different
frequency resolution methods and time resolution properties.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrogram"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Click the **Spectrogram** tab on the Spectrum Analyzer toolstrip.
In the **Time Options** section, set the **Time Resolution
(s)** to `Auto`

or enter a positive scalar.

To enable the **Time Resolution (s)**, select
**Spectrogram** in the **Analyzer**
tab.

**Data Types: **`char`

| `string`

`TimeResolution`

— Time resolution

`0.001`

(default) | positive scalar

Specify the time resolution of each spectrogram line as a positive scalar, expressed in seconds.

The Spectrum Analyzer determines the time resolution value based on the frequency resolution method, RBW, and time resolution properties.

Method | RBW | Time Resolution | Resulting Time Resolution in Seconds |
---|---|---|---|

`Welch` or ```
Filter
Bank
``` | `Auto` | `Auto` | 1/RBW |

`Welch` or ```
Filter
Bank
``` | `Auto` | Manually entered | 1/Time Resolution Hz |

`Welch` or ```
Filter
Bank
``` | Manually entered | `Auto` | 1/RBW seconds |

`Welch` or ```
Filter
Bank
``` | Manually entered | Manually entered | Equal to or greater than the minimum attainable time resolution 1/RBW. The Spectrum Analyzer combines several spectral estimates into one spectrogram line to obtain the desired time resolution. It uses interpolation to obtain time resolution values that are not integer multiples of 1/RBW. |

**Tunable: **Yes

#### Dependency

To enable this property, set:

`ViewType`

to`"Spectrogram"`

or`"Spectrum and spectrogram"`

`TimeResolutionSource`

to`"Property`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Spectrogram
options** section, in the **Time res (s)** box, enter a
number.

`TimeSpanSource`

— Source of time span value

`"Auto"`

(default) | `"Property"`

Source for the time span of the spectrogram, specified as either
`"Auto"`

or `"Property"`

. If you set this property
to `"Auto"`

, the spectrogram displays 100 spectrogram lines at any
given time. If you set this property to `"Property"`

, the spectrogram
uses the time duration you specify in seconds in the `TimeSpan`

property.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrogram"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Click the **Spectrogram** tab on the Spectrum Analyzer toolstrip.
In the **Time Options** section, set the **Time Span
(s)** to `Auto`

or enter a positive scalar.

**Data Types: **`char`

| `string`

`TimeSpan`

— Time span

`0.1`

(default) | positive scalar

Specify the time span of the spectrogram display in seconds. You must set the time span to be at least twice as large as the duration of the number of samples required for a spectral update.

**Tunable: **Yes

#### Dependency

To enable this property, set:

`ViewType`

to`"Spectrogram"`

or`"Spectrum and spectrogram"`

.`TimeSpanSource`

to`"Property"`

.

#### Scope Window Use

Open the **Spectrum Settings**. In the **Spectrogram
options** section, in the **Time span (s)** box, enter a
number.

### Measurements

`MeasurementChannel`

— Channel for which measurements are obtained

`1`

(default) | positive integer

Channel for which the measurements are obtained, specified as a real, positive integer greater than 0 and less than or equal to 100. The maximum number you can specify is the number of channels (columns) in the input signal.

**Tunable: **Yes

#### Scope Window Use

Click on **Tools** > **Measurements** and
open the **Trace Selection** settings.

**Data Types: **`double`

`SpectralMask`

— Spectral mask lines

`SpectralMaskSpecification`

object

Specify whether to display upper and lower spectral mask lines on a spectrum plot.
This property uses properties from a `SpectralMaskSpecification`

object to enable and configure the spectral
masks.

**Tunable: **Yes

#### Scope Window Use

Open the **Spectral Mask** pane and modify the
**Settings** options.

`PeakFinder`

— Peak finder measurement

`PeakFinderConfiguration`

object

Peak finder measurement, specified as a `PeakFinderConfiguration`

object. Enable peak finder to compute and display
the largest calculated peak values. All `PeakFinderConfiguration`

properties are tunable.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrum"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Click the **Measurements** tab on the Spectrum Analyzer toolstrip and modify the peak finder measurements in the **Peaks** section.

The **Measurements** tab appears when you select
**Spectrum** in the **Scope** tab.

`CursorMeasurements`

— Cursor measurements

`CursorMeasurementsConfiguration`

object

Cursor measurements, specified as a `CursorMeasurementsConfiguration`

object. Enable cursor measurements to display waveform cursors. All
`CursorMeasurementsConfiguration`

properties are
tunable.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to `"Spectrum"`

or
`"Spectrum and spectrogram"`

.

#### Scope Window Use

Click the **Measurements** tab on the Spectrum Analyzer toolstrip and modify the cursor measurements in the **Cursors** section.

The **Measurements** tab appears when you select
**Spectrum** in the
**Scope** tab.

`ChannelMeasurements`

— Channel measurements

`ChannelMeasurementsSpecification`

object

Enable channel measurements to compute and display the occupied bandwidth or adjacent channel power ratio. The `ChannelMeasurements`

property uses the `ChannelMeasurementsSpecification`

properties.

The `ChannelMeasurementsSpecification`

properties are:

`Algorithm`

–– Type of measurement data to display, specified as either`"Occupied BW"`

or`"ACPR"`

.Default:

`"Occupied BW"`

`FrequencySpan`

–– Frequency span mode, specified as either`"Span and center frequency"`

or`"Start and stop frequencies"`

Default:

`"Span and center frequency"`

`Span`

–– Frequency span over which the channel measurements are computed, specified as a real, positive scalar in Hz. This property applies when you set the`FrequencySpan`

property to`"Span and center frequency"`

.Default:

`2000`

Hz`CenterFrequency`

–– Center frequency of the span over which the channel measurements are computed, specified as a real scalar in Hz. This property applies when you set the`FrequencySpan`

property to`"Span and center frequency"`

.Default:

`0`

Hz`StartFrequency`

–– Start frequency over which the channel measurements are computed, specified as a real scalar in Hz. This property applies when you set the`FrequencySpan`

property to`"Start and stop frequencies"`

.Default:

`-1000`

Hz`StopFrequency`

–– Stop frequency over which the channel measurements are computed, specified as a real scalar in Hz. This property applies when you set the`FrequencySpan`

property to`"Start and stop frequencies"`

.Default:

`1000`

Hz`PercentOccupiedBW`

–– Percent of power over which to compute the occupied bandwidth, specified as a positive real scalar. This property applies when you set the`Algorithm`

property to`"Occupied BW"`

.Default:

`99`

`NumOffsets`

–– Number of adjacent channel pairs, specified as a real, positive integer. This property applies when you set the`Algorithm`

property to`"ACPR"`

.Default:

`2`

`AdjacentBW`

–– Adjacent channel bandwidth, specified as a real, positive scalar. This property applies when you set the`Algorithm`

property to`"ACPR"`

.Default:

`1000`

`FilterShape`

–– Filter shape for both main and adjacent channels, specified as`"None"`

,`"Gaussian"`

, or`"RRC"`

. This property applies when you set the`Algorithm`

property to`"ACPR"`

.Default:

`"None"`

`FilterCoeff`

–– Channel filter coefficient, specified as a real scalar between`0`

and`1`

. This property applies when you set the`Algorithm`

property to`"ACPR"`

and the`FilterShape`

property to either`"Gaussian"`

or`"RRC"`

.Default:

`0.5`

`ACPROffsets`

–– Frequency of the adjacent channel relative to the center frequency of the main channel, specified as a real vector of length equal to the number of offset pairs specified in`NumOffsets`

. This property applies when you set the`Algorithm`

property to`"ACPR"`

.Default:

`[2000 3500]`

`Enable`

–– Set this property to`true`

to enable channel measurements. Valid values are`true`

or`false`

.Default:

`false`

All `ChannelMeasurementsSpecification`

properties are tunable.

#### Scope Window Use

Open the **Channel Measurements** pane () and modify the **Measurement**
and **Channel Settings** options.

`DistortionMeasurements`

— Distortion measurements

`DistortionMeasurementsConfiguration`

object

Distortion measurements, specified as a `DistortionMeasurementsConfiguration`

object. Enable distortion measurements
to compute and display the harmonic distortion and intermodulation distortion. All
`DistortionMeasurementsConfiguration`

properties are tunable.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to `"Spectrum"`

or
`"Spectrum and spectrogram"`

.

#### Scope Window Use

Click the **Measurements** tab on the Spectrum Analyzer toolstrip and modify the distortion measurements in the **Distortion** section.

The **Measurements** tab appears when you select
**Spectrum** in the **Scope** tab.

### Visualization

`Name`

— Caption to display in spectrum Analyzer window

`"Spectrum Analyzer"`

(default) | character vector | string scalar

Caption to display in the scope window, specified as a character vector or string scalar.

**Tunable: **Yes

**Data Types: **`char`

| `string`

`Position`

— Window position

screen center (default) | `[left bottom width height]`

Spectrum Analyzer window position in pixels, specified by the size and location of the scope window as a four-element double vector of the form [left bottom width height]. You can place the scope window in a specific position on your screen by modifying the values to this property.

By default, the window appears in the center of your screen with a width of `800`

pixels and height
of `450`

pixels. The exact center coordinates depend on your screen resolution.

**Tunable: **Yes

`PlotType`

— Plot type to display normal traces

`"Line"`

(default) | `"Stem"`

Plot type to display normal traces, specified as `"Line"`

or
`"Stem"`

. Normal traces are traces that display free-running
spectral estimates.

**Tunable: **Yes

#### Dependencies

To enable this property, set:

`ViewType`

to`"Spectrum"`

or`"Spectrum and spectrogram"`

.`PlotNormalTrace`

to`true`

.

#### Scope Window Use

Click the **Scope** tab on the Spectrum Analyzer toolstrip,
navigate to the **Configuration** section and click
**Settings**. In the Spectrum Analyzer Settings window, under
**Display and Labels**, set **Plot Type** to
`Line`

or `Stem`

.

To enable the **Plot
Type**, you must:

Select

**Spectrum**in the**Views**section of the**Scope**tab.Enable the

**Normal Trace**check box in the**Trace Options**section of the**Spectrum**tab.

**Data Types: **`char`

| `string`

`PlotNormalTrace`

— Normal trace flag

`true`

(default) | `false`

To remove normal traces from the display, set this property to
`false`

. These traces display the free-running spectral estimates.
The Spectrum Analyzer continues its spectral computations even when you set this
property to `false`

.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrum"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Click the **Spectrum** tab on the Spectrum Analyzer toolstrip and
select the **Normal Trace** check box in the **Trace
Options** section.

To enable the **Normal Trace** check box, select
**Spectrum** in the **Analyzer** tab.

**Data Types: **`logical`

`PlotMaxHoldTrace`

— Max-hold trace flag

`false`

(default) | `true`

To compute and plot the maximum-hold spectrum of each input channel, set this property to `true`

.
The maximum-hold spectrum at each frequency bin is computed by keeping the maximum value of all the power spectrum
estimates. When you toggle this property, the Spectrum Analyzer resets its maximum-hold computations.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrum"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Click the **Spectrum** tab on the Spectrum Analyzer toolstrip and
select the **Max-Hold Trace** check box in the **Trace
Options** section.

To enable the **Max-Hold Trace** check box, select
**Spectrum** in the **Analyzer** tab.

**Data Types: **`logical`

`PlotMinHoldTrace`

— Min-hold trace flag

`false`

(default) | `true`

To compute and plot the minimum-hold spectrum of each input channel, set this property to `true`

.
The minimum-hold spectrum at each frequency bin is computed by keeping the minimum value of all the power spectrum
estimates. When you toggle this property, the Spectrum Analyzer resets its minimum-hold computations.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrum"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Click the **Spectrum** tab on the Spectrum Analyzer toolstrip and
select the **Min-Hold Trace** check box in the **Trace
Options** section.

To enable the **Min-Hold Trace** check box, select
**Spectrum** in the **Analyzer** tab.

**Data Types: **`logical`

`Title`

— Display title

`''`

(default) | character vector | string scalar

Display title, specified as a character vector or a string scalar.

**Tunable: **Yes

#### Scope Window Use

Click the **Scope** tab on the spectrum analyzer toolstrip. In
the **Configuration** section, click
**Settings**, and enter **Title**.

**Data Types: **`char`

| `string`

`YLabel`

— Y-axis label

`''`

(default) | character vector | string scalar

*y*-axis label, specified as a character vector or a string scalar.
The Spectrum Analyzer displays the label to the left of the
*y*-axis.

Regardless of the value of this property, Spectrum Analyzer always displays power
units as one of the `SpectrumUnits`

values.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to
`"Spectrum"`

or ```
"Spectrum and
spectrogram"
```

.

#### Scope Window Use

Click the **Scope** tab on the Spectrum Analyzer toolstrip. In
the **Configuration** section, click
**Settings**. In the Spectrum Analyzer Settings window that
opens up, under **Display and labels**, enter
**Y-Label**.

To enable the **Y-Label**, select
**Spectrum** in the **Scope** tab.

**Data Types: **`char`

| `string`

`ShowLegend`

— Flag to show legend

`false`

(default) | `true`

Flag to show the legend, specified as `true`

or
`false`

. To show a legend with the input names, set this property
to `true`

.

Use the legend to control which signals are visible. In the scope legend, click a
signal name to hide the signal in the scope. To show the signal, click the signal name
again. To show only one signal, right-click the signal name. To show all signals, press
**Esc**.

**Tunable: **Yes

#### Dependencies

To enable this property, set the `ViewType`

property to
`"Spectrum"`

or `"Spectrum and spectrogram"`

.

#### Scope Window Use

Click the **Scope** tab on the Spectrum Analyzer toolstrip. To
see the legend, click **Legend** in the
**Configuration** section.

To enable the **Legend**, select
**Spectrum** in the **Scope** tab.

**Data Types: **`logical`

`ChannelNames`

— Channel names

empty cell (default) | cell array of character vectors | array of strings

Channel names in the input data, specified as a cell array of character vectors or an array of strings. The names you specify in this property appear in the following locations:

Legend

**Spectrum Analyzer Settings**>**Color and styling**section**Measurements**and**Channel Measurements**tabs

If you do not specify channel names, the
spectrum analyzer names the channels as `Channel 1`

, ```
Channel
2
```

, and so on.

**Tunable: **Yes

#### Dependency

To see the channel names, set `ShowLegend`

to
`true`

.

#### Scope Window Use

Click the **Scope** tab on the spectrum analyzer toolstrip. To
see the legend, click **Legend** in the
**Configuration** section.

**Data Types: **`char`

`ShowGrid`

— Flag to show grid

`true`

(default) | `false`

Flag to show the grid, specified as `true`

or
`false`

. Set this property to `true`

to show grid
lines in the plot.

**Tunable: **Yes

#### Scope Window Use

Click the **Scope** tab on the Spectrum Analyzer toolstrip. In
the **Configuration** section, click
**Settings**, and select **Show
Grid**.

**Data Types: **`logical`

`YLimits`

— Y-axis limits

`[-80, 20]`

(default) | `[ymin ymax]`

*y*-axis limits, specified as a two-element numeric vector of the
form [`ymin ymax`

]. The units of the *y*-axis limits
depend on the `SpectrumUnits`

property.

**Example: **`scope.YLimits = [-10,20]`

**Tunable: **Yes

#### Dependencies

To enable this property, set the

`ViewType`

property to`"Spectrum"`

or`"Spectrum and spectrogram"`

.The units directly depend upon the

`SpectrumUnits`

property.

#### Scope Window Use

Click the **Scope** tab on the Spectrum Analyzer toolstrip. In
the **Configuration** section, click
**Settings**. In the Spectrum Analyzer Settings window that
opens up, under **Display and Labels**, enter
**Y-Limits**.

To enable the **Y-Limits**, select
**Spectrum** in the **Scope** tab.

`ColorLimits`

— Scale spectrogram color limits

`[-80, 20]`

(default) | `[colorMin colorMax]`

Color limits of the spectrogram, specified as a two-element numeric vector of the form
[`colorMin colorMax`

]. The units of the color limits directly
depend upon the `SpectrumUnits`

property.

**Example: **`scope.ColorLimits = [-10,20]`

**Tunable: **Yes

#### Dependencies

To enable this property, set the

`ViewType`

property to`"Spectrogram"`

or`"Spectrum and spectrogram"`

.The units directly depend upon the

`SpectrumUnits`

property.

#### Scope Window Use

Click the **Analyzer** tab on the Spectrum Analyzer toolstrip. In
the **Configuration** section, click
**Settings**. In the Spectrum Analyzer Settings window that
opens up, under **Display and Labels**, enter **Color
Limits**.

To enable the **Color Limits**, select
**Spectrogram** in the **Analyzer**
tab.

`AxesScaling`

— Axes scaling mode

`"Auto"`

(default) | `"Manual"`

| `"OnceAtStop"`

| `"Updates"`

Axes scaling mode, specified as one of these:

`"Auto"`

— The scope scales the axes to fit the data, both during and after simulation.`"Manual"`

— The scope does not scale the axes automatically.`"OnceAtStop"`

— The scope scales the axes when the simulation stops.`"Updates"`

— The scope scales the axes after a specific number of visual updates. It determines the number of updates using the`AxesScalingNumUpdates`

property.

**Tunable: **Yes

**Data Types: **`char`

| `string`

`AxesLayout`

— Orientation of the spectrum and spectrogram

`"Vertical"`

(default) | `"Horizontal"`

Layout of the axes, specified as one of `"Vertical"`

or
`"Horizontal"`

. A vertical layout stacks the spectrum above the
spectrogram. A horizontal layout puts the two views side-by-side.

**Tunable: **Yes

#### Dependency

To enable this property, set `ViewType`

to ```
"Spectrum
and spectrogram"
```

.

#### Scope Window Use

Click the **Analyzer** tab on the Spectrum Analyzer toolstrip.
Select **Spectrum** and **Spectrogram**. In the
**Configuration** section, select and update
**Layout**.

**Data Types: **`char`

| `string`

## Usage

### Description

`scope(`

updates the spectrum of the
signal in the spectrum analyzer.`signal`

)

`scope(signal1,signal2,...,signalN)`

displays multiple signals in
the spectrum analyzer. The signals must have the same frame length, but can vary in number
of channels. You must set the `NumInputPorts`

property to enable
multiple input signals.

### Input Arguments

`signal`

— Input signal or signals to visualize

scalar | vector | matrix

Specify one or more input signals to visualize in the
`dsp.SpectrumAnalyzer`

. Signals can have a different number of channels, but
must have the same frame length.

**Example: **`scope(signal1, signal2)`

**Data Types: **`single`

| `double`

| `int8`

| `int16`

| `int32`

| `int64`

| `uint8`

| `uint16`

| `uint32`

| `uint64`

| `fi`

## Object Functions

To use an object function, specify the
System object as the first input argument. For
example, to release system resources of a System object named `obj`

, use
this syntax:

release(obj)

### Specific to dsp.SpectrumAnalyzer

`generateScript` | Generate MATLAB script to create scope with current settings |

`getMeasurementsData` | Get the current measurement data displayed on the spectrum analyzer |

`getSpectralMaskStatus` | Get test results of current spectral mask |

`getSpectrumData` | Save spectrum data shown in spectrum analyzer |

`isNewDataReady` | Check spectrum analyzer for new data |

### Specific to Scopes

If you want to restart the simulation from the beginning, call `reset`

to
clear the scope window displays. Do not call `reset`

after calling
`release`

.

## Examples

### Spectrum Analyzer for One-Sided Power Spectrum

View a one-sided power spectrum made from the sum of fixed real sine waves with different amplitudes and frequencies.

Fs = 100e6; % Sampling frequency fSz = 5000; % Frame size sin1 = dsp.SineWave(1e0, 5e6,0,'SamplesPerFrame',fSz,'SampleRate',Fs); sin2 = dsp.SineWave(1e-1,15e6,0,'SamplesPerFrame',fSz,'SampleRate',Fs); sin3 = dsp.SineWave(1e-2,25e6,0,'SamplesPerFrame',fSz,'SampleRate',Fs); sin4 = dsp.SineWave(1e-3,35e6,0,'SamplesPerFrame',fSz,'SampleRate',Fs); sin5 = dsp.SineWave(1e-4,45e6,0,'SamplesPerFrame',fSz,'SampleRate',Fs); scope = dsp.SpectrumAnalyzer; scope.SampleRate = Fs; scope.SpectralAverages = 1; scope.PlotAsTwoSidedSpectrum = false; scope.RBWSource = 'Auto'; scope.PowerUnits = 'dBW'; for idx = 1:1e2 y1 = sin1(); y2 = sin2(); y3 = sin3(); y4 = sin4(); y5 = sin5(); scope(y1+y2+y3+y4+y5+0.0001*randn(fSz,1)); end

Run the `release`

method to let property values and input
characteristics change. The scope automatically scales the axes.

release(scope)

Run the `clear`

function to close the Spectrum Analyzer
window.

`clear('scope');`

### Spectrum Analyzer For Two-Sided Power Spectrum

View a two-sided power spectrum of a sine wave with noise on the Spectrum Analyzer.

sin = dsp.SineWave('Frequency',100,'SampleRate',1000); sin.SamplesPerFrame = 1000; scope = dsp.SpectrumAnalyzer('SampleRate',sin.SampleRate); for ii = 1:250 x = sin() + 0.05*randn(1000,1); scope(x); end

Run the `release`

method to change property values and input
characteristics. The scope automatically scales the axes. It updates the display one
more time if any data is in the internal buffer.

release(scope);

Run the MATLAB `clear`

function to close the Spectrum Analyzer
window.

`clear('scope');`

### Spectrogram of Chirp Signal

This example shows the spectrogram for a chirp signal with added random noise.

Fs = 233e3; frameSize = 20e3; chirp = dsp.Chirp('SampleRate',Fs,... 'SamplesPerFrame',frameSize,... 'InitialFrequency',11e3,... 'TargetFrequency',11e3+55e3); scope = dsp.SpectrumAnalyzer('SampleRate',Fs); scope.ViewType = 'Spectrogram'; scope.RBWSource = 'Property'; scope.RBW = 500; scope.TimeSpanSource = 'Property'; scope.TimeSpan = 2; scope.PlotAsTwoSidedSpectrum = false; for idx = 1:50 y = chirp()+ 0.05*randn(frameSize,1); scope(y); end release(scope)

### Display Frequency Input from Spectral Estimation

Use the Spectrum Analyzer to display frequency input from spectral estimates of sinusoids embedded in white Gaussian noise.

**Initialization**

Initialize two `dsp.SpectrumEstimator`

objects to display. Set one
object to use the Welch-based spectral estimation technique with a Hann window, set the
other object use a filter bank estimation. Specify a noisy sine wave input signal with
four sinusoids at 0.16, 0.2, 0.205, and 0.25 cycles/sample. View the spectral estimate
using a third object, a spectrum analyzer, set to process frequency input.

FrameSize = 420; Fs = 1; Frequency = [0.16 0.2 0.205 0.25]; sinegen = dsp.SineWave('SampleRate',Fs,'SamplesPerFrame',FrameSize,... 'Frequency',Frequency,'Amplitude',[2e-5 1 0.05 0.5]); NoiseVar = 1e-10; numAvgs = 8; hannEstimator = dsp.SpectrumEstimator('PowerUnits','dBm',... 'Window','Hann','FrequencyRange','onesided',... 'SpectralAverages',numAvgs,'SampleRate',Fs); filterBankEstimator = dsp.SpectrumEstimator('PowerUnits','dBm',... 'Method','Filter bank','FrequencyRange','onesided',... 'SpectralAverages',numAvgs,'SampleRate',Fs); spectrumPlotter = dsp.SpectrumAnalyzer('InputDomain','Frequency',... 'SampleRate',Fs,... 'SpectrumUnits','dBm','YLimits',[-120,40],... 'PlotAsTwoSidedSpectrum',false,... 'ChannelNames',{'Hann window','Filter bank'},'ShowLegend',true);

**Streaming**

Stream the input. Compare the spectral estimates in the spectrum analyzer.

for i = 1:1000 x = sum(sinegen(),2) + sqrt(NoiseVar)*randn(FrameSize,1); Pse_hann = hannEstimator(x); Pfb = filterBankEstimator(x); spectrumPlotter([Pse_hann,Pfb]) end

### Obtain Measurement Data Programmatically for `dsp.SpectrumAnalyzer`

System object

Compute and display the power spectrum of a noisy sinusoidal input
signal using the `dsp.SpectrumAnalyzer`

System object. Measure the peaks, cursor placements, adjacent channel power ratio, and
distortion in the spectrum by enabling the following properties:

`PeakFinder`

`CursorMeasurements`

`ChannelMeasurements`

`DistortionMeasurements`

**Initialization**

The input sine wave has two frequencies: 1000 Hz and 5000 Hz. Create two
`dsp.SineWave`

System objects to generate these two frequencies.
Create a `dsp.SpectrumAnalyzer`

System object to compute and display
the power spectrum.

Fs = 44100; Sineobject1 = dsp.SineWave('SamplesPerFrame',1024,... 'PhaseOffset',10,... 'SampleRate',Fs,'Frequency',1000); Sineobject2 = dsp.SineWave('SamplesPerFrame',1024,... 'SampleRate',Fs,'Frequency',5000); SA = dsp.SpectrumAnalyzer('SampleRate',Fs,'Method','Filter bank',... 'SpectrumType','Power','PlotAsTwoSidedSpectrum',false,... 'ChannelNames',{'Power spectrum of the input'},... 'YLimits',[-120 40],'ShowLegend',true);

**Enable Measurements Data**

To obtain the measurements, set the `Enable`

property of the
measurements to `true`

.

SA.CursorMeasurements.Enable = true; SA.ChannelMeasurements.Enable = true; SA.PeakFinder.Enable = true; SA.DistortionMeasurements.Enable = true;

**Use ****getMeasurementsData**

Stream in the noisy sine wave input signal and estimate the power spectrum of the
signal using the spectrum analyzer. Measure the characteristics of the spectrum. Use the
`getMeasurementsData`

function to obtain these measurements
programmatically. The `isNewDataReady`

function indicates when there is
new spectrum data. The measured data is stored in the variable
`data`

.

data = []; for Iter = 1:1000 Sinewave1 = Sineobject1(); Sinewave2 = Sineobject2(); Input = Sinewave1 + Sinewave2; NoisyInput = Input + 0.001*randn(1024,1); SA(NoisyInput); if SA.isNewDataReady data = [data;getMeasurementsData(SA)]; end end

The right side of the spectrum analyzer shows the enabled measurement panes. The
values shown in these panes match with the values shown in the last time step of the
`data`

variable. You can access the individual fields of
`data`

to obtain the various measurements programmatically.

**Compare Peak Values**

Peak values are obtained by the `PeakFinder`

property. Verify that
the peak values obtained in the last time step of `data`

match the
values shown on the spectrum analyzer plot.

peakvalues = data.PeakFinder(end).Value

`peakvalues = `*3×1*
26.9851
24.1735
-51.1973

frequencieskHz = data.PeakFinder(end).Frequency/1000

`frequencieskHz = `*3×1*
4.9957
0.9905
0.2369

## Tips

To close the scope window and clear its associated data, use the MATLAB

`clear`

function.To hide or show the scope window, use the

`hide`

and`show`

functions.Use the MATLAB

`mcc`

function to compile code containing a Spectrum Analyzer.You cannot open Spectrum Analyzer configuration dialog boxes if you have more than one compiled component in your application.

## Algorithms

### Spectrum Estimation — Filter Bank

When you choose the `Filter Bank`

method, the spectrum
analyzer uses an analysis filter bank to estimate the power spectrum.

The filter bank splits the broadband input signal *x(n)*, of sample
rate *fs*, into multiple narrow band signals
*y _{0}(m)*,

*y*, … ,

_{1}(m)*y*, of sample rate

_{M-1}(m)*fs/M*.

The variable *M* represents the number of frequency bands in the
filter bank. In the spectrum analyzer, *M* is equal to the number of
data points needed to achieve the specified RBW value or 1024, whichever is larger. For
more information on the analysis filter bank and its implementation, see the More About and the Algorithm sections in the
`dsp.Channelizer`

object.

After the spectrum analyzer splits the broadband input signal into multiple narrow
bands, it computes the power in each narrow frequency band using the following equation.
Each *Z _{i}* value is the power estimate over that
narrow frequency band.

$${Z}_{i}=\frac{1}{L}{\displaystyle \sum _{m=0}^{L-1}{\left|{y}_{i}[m]\right|}^{2}}$$

*L* is length of the narrowband signal
*y _{i}(m)* and

*i*= 1, 2, …,

*M*−1.

The power values in all the narrow frequency bands (denoted by
*Z _{i}*) form the

*Z*vector.

$$Z=[{Z}_{0},\text{\hspace{0.17em}}{Z}_{1},\text{\hspace{0.17em}}{Z}_{2},\cdots ,{Z}_{M-1}]$$

The spectrum analyzer averages the current *Z* vector with the
previous *Z* vectors using one of the two moving average methods: video
bandwidth or exponential weighting. The output of the averaging operation forms the
spectral estimate vector. For details on the two averaging methods, see Averaging Method.

The spectrum analyzer uses the value you specify in the **RBW (Hz)**
parameter or the **Number of frequency bands** parameter to determine
the input frame length.

When you specify the **Resolution Method** to
`RBW`

, and you set **RBW (Hz)** to:

`Auto`

–– The spectrum analyzer determines the appropriate resolution bandwidth to ensure that there are 1024 RBW intervals over the specified frequency span. When you set**RBW (Hz)**to`Auto`

, the spectrum analyzer calculates RBW using this equation.$$RB{W}_{auto}=\frac{span}{1024}$$

scalar value –– The spectrum analyzer calculates the number of samples

*N*using this equation._{samples}$${N}_{samples}=\frac{{F}_{s}}{RBW}$$

*F*is the sample rate of the input signal as specified in the_{s}**Sample Rate (Hz)**property.The RBW value you specify must be such that there are at least two RBW intervals over the specified frequency span. The ratio of the overall span to RBW must be greater than two.

$$\frac{span}{RBW}>2$$

*span*is the frequency span over which the spectrum analyzer computes and plots the spectrum. To view the**Span (Hz)**in the scope, click the**Estimation**tab on the spectrum analyzer toolstrip and navigate to the**Frequency Options**section. To enable this property, set**Frequency Span**to`Span and Center Frequency`

.

When you specify the **Resolution Method** to ```
Number of
frequency bands
```

, the resulting RBW is given by:

$$RBW\text{}=\frac{Fs}{FFTLength}$$

When the number of input samples is not sufficient to achieve the specified resolution bandwidth, the spectrum analyzer adjusts its RBW value according to the number of input samples provided and displays a message similar to this one. The spectrum analyzer removes this message once you provide enough input samples.

### Spectrum Estimation — Welch's Method

When you select the `Welch`

method, the power spectrum estimate is
the averaged modified periodograms.

The algorithm in the spectrum analyzer consists of these steps:

The block buffers the input into

*N*-point data segments. Each data segment is split into*P*overlapping data segments, each of length*M*, overlapping by*D*points. The data segments can be represented as:$$\begin{array}{l}{x}_{i}(n)=x(n+iD),\text{\hspace{1em}}\text{\hspace{0.05em}}n=0,1,\mathrm{...},M-1\\ \text{\hspace{1em}}\text{\hspace{1em}}\text{\hspace{1em}}\text{\hspace{1em}}\text{\hspace{1em}}\text{\hspace{1em}}\text{\hspace{1em}}\text{\hspace{1em}}i=0,1,\mathrm{...},P-1\end{array}$$

If

*D*=*M*/2, the overlap is 50%.If

*D*= 0, the overlap is 0%.

Apply a window to each of the

*P*overlapping data segments in the time domain.If you set the

**Resolution Method**to`Window length`

, you can specify the data window length*N*using the_{window}**Window Length**parameter in the**Estimation**tab.If you set the

**Resolution Method**to`RBW`

, the algorithm determines the data window length using this equation, $${N}_{window}=\frac{NENBW\times Fs}{RBW}$$.Then, it partitions the input signal into a number of windowed data segments.

Most window functions afford more influence to the data at the center of the set than to the data at the edges, which represents a loss of information. To mitigate that loss, the individual data sets are commonly overlapped in time. For each windowed segment, compute the periodogram by computing the discrete Fourier transform. Then compute the squared magnitude of the result and divide the result by

*M*.$${P}_{xx}^{i}(f)=\frac{1}{MU}{\left|{\displaystyle \sum _{n=0}^{M-1}{x}_{i}(n)w(n){e}^{-j2\pi fn}}\right|}^{2},\text{\hspace{1em}}\text{\hspace{1em}}i=0,1,\mathrm{...},P-1$$

where U is the normalization factor for the power in the window function and is given by

$$U=\frac{1}{M}{\displaystyle \sum _{n=0}^{M-1}{w}^{2}(n)}$$

You can specify the window using the

**Window**parameter in the**Estimation**tab of the spectrum analyzer toolstrip.The spectrum analyzer calculates and plots the power spectrum, power spectrum density, and RMS using the modified

*Periodogram*estimator. For more information about the Periodogram method, see`periodogram`

.To determine the power spectrum estimate for Welch's method, the spectrum analyzer averages the result of the periodograms for the last

*P*data segments. The averaging reduces the variance, compared to the original*N*-point data segment. For more details on the averaging, see Averaging Method.$$\mathrm{PSD}\left(f\right)=\frac{1}{P}{\displaystyle \sum _{i=0}^{P-1}{P}_{xx}^{i}(f)}$$

The spectrum analyzer computes the power spectral density using:

$$\mathrm{PSD}\left(f\right)=\frac{1}{P*{F}_{s}}{\displaystyle \sum _{i=0}^{P-1}{P}_{xx}^{i}(f)}$$

The power spectrum is the product of the power spectral density and the resolution bandwidth, as given by this equation.

$${P}_{spectrum}\left(f\right)=\mathrm{PSD}\left(f\right)\times RBW=\mathrm{PSD}\left(f\right)\times \frac{{F}_{s}\times NENBW}{{N}_{window}}$$

The spectrum analyzer plots the power as a spectrogram in the

**Spectrogram**mode. Each line of the spectrogram is one periodogram. The time resolution of each line is 1/*RBW*, which is the minimum attainable resolution. Achieving the resolution you want might require combining several periodograms. You then use interpolation to calculate noninteger values of 1/*RBW*. In the spectrogram display, time scrolls from top to bottom, so the most recent data appears at the top of the display. The offset shows the time value at which the center of the most current spectrogram line occurred.

The spectrum analyzer uses a certain number of samples to compute a spectral estimate. This value is directly related to the resolution bandwidth (RBW) using this equation, $${N}_{samples}=\frac{\left(1-\frac{{O}_{p}}{100}\right)\times NENBW\times {F}_{s}}{RBW}$$

or to the window length
(*N _{window}*) using this equation,

$${N}_{samples}=\left(1-\frac{{O}_{p}}{100}\right){N}_{window}$$

where O_{p} is the overlap percentage, NENBW is the normalized
effective noise bandwidth, F_{s} is the input sample rate, and RBW is the resolution
bandwidth.

The spectrum analyzer shows the number of samples per update in the spectrum analyzer status bar.

When you specify the **Resolution
Method** to `RBW`

, the window length is given
by,

$${N}_{window}=\frac{NENBW\times {F}_{s}}{RBW}$$

When you specify the **Resolution
Method** to `Window length`

, the algorithm uses
the window length value you specify in the **Window Length** parameter
in the **Estimation** tab on the spectrum analyzer toolstrip.

### Overlap Percentage (*O*_{p})

_{p}

The overlap percentage *O _{p}* is the value you
specify in the

**Overlap %**property. To view the

**Overlap %**in the scope, click the

**Estimation**tab on the spectrum analyzer toolstrip and navigate to the

**Window Options**section.

When you increase the overlap percentage, the spectrum analyzer needs fewer new input samples to compute a new spectral update.

O_{p} | N_{samples} |
---|---|

0% | 100 |

50% | 50 |

80% | 20 |

### Normalized Effective Noise Bandwidth (NENBW)

The normalized effective noise bandwidth *NENBW* is a window
parameter that measures the noise performance of the window. NENBW is determined using
the window length and the window coefficients, and is given by the following
equation:

$$NENBW={N}_{window}\times \frac{{\displaystyle \sum _{n=1}^{{N}_{window}}{w}^{2}(n)}}{{\left[{\displaystyle \sum _{n=1}^{{N}_{window}}w(n)}\right]}^{2}}$$

*w*(*n*) denotes the vector of window coefficients.
*N _{window}* is the window length. For more
information on how the algorithm determines the window length, see the Spectrum
Estimation –– Welch's Method section in Algorithms.

The rectangular window has the smallest NENBW, with a value of 1. All other windows have a larger NENBW value. For example, the Hann window has an NENBW value of approximately 1.5.

The spectrum analyzer shows the value of *NENBW* in the spectrum
analyzer status bar.

You can enable *NENBW* only when you set
**Input Domain** to `Time`

and
**Estimation Method** to `Welch`

in the
**Estimation** tab on the spectrum analyzer toolstrip.

### Input Sample Rate (*Fs*)

*F _{s}* is the sample rate of the input signal.
To view the

**Sample Rate (Hz)**in the scope, click the

**Scope**tab on the spectrum analyzer toolstrip and navigate to the

**Bandwidth**section. You can enable this property in the status bar at the bottom of the spectrum analyzer window. Click the icon in the status bar and select

```
Sample
Rate
```

.### Resolution Bandwidth (RBW)

Resolution bandwidth controls the spectral resolution of the displayed signal. The RBW value determines the spacing between frequencies that the scope can resolve. A smaller value gives a higher spectral resolution and lowers the noise floor, that is, the spectrum analyzer can resolve frequencies that are closer to each other. However, this comes at the cost of a longer sweep time.

You can specify the resolution bandwidth using the **RBW (Hz)**
parameter.

If you specify the window length, the scope determines the RBW value from the window length using this equation, $$RBW=\frac{NENBW\times Fs}{{N}_{window}}$$.

When you specify the **Resolution
Method** to `RBW`

, and you set **RBW
(Hz)** to:

`Auto`

–– The spectrum analyzer determines the appropriate resolution bandwidth to ensure that there are 1024 RBW intervals over the specified frequency span. When you set**RBW (Hz)**to`Auto`

, the spectrum analyzer calculates using this equation.$$RB{W}_{auto}=\frac{span}{1024}$$

scalar value –– Specify a value such that there are at least two RBW intervals over the specified frequency span. The ratio of the overall span to RBW must be greater than two:

$$\frac{span}{RBW}>2$$

*span* is the frequency span over which the spectrum analyzer
computes and plots the spectrum. Spectrum analyzer shows the span through the
**Span (Hz)** property. To view the **Span (Hz)**
in the scope, click the **Estimation** tab on the spectrum analyzer
toolstrip, navigate to the **Frequency Options** section, and set
**Frequency Span** to ```
Span and Center
Frequency
```

.

When you specify the **Resolution
Method** to `Number of frequency bands`

, the
resulting RBW is given by:

$$RBW\text{}=\frac{Fs}{FFTLength}$$

When the number of input samples is not sufficient to achieve the specified resolution bandwidth, the spectrum analyzer adjusts its RBW value according to the number of input samples provided and displays a message similar to this one. The spectrum analyzer removes this message once you provide enough input samples.

You can enable this property in the status bar at the bottom of the spectrum analyzer
window. Click the icon in the status bar and select
`RBW`

.

### Nyquist Frequency Interval

When you plot the two-sided spectrum by selecting **Two-Sided Spectrum** in
the **Spectrum**
or **Spectrogram** tab, the Nyquist
frequency interval is $$\left[-\frac{SampleRate}{2},\frac{SampleRate}{2}\right]+FrequencyOffset$$ Hz.

When you clear the **Two-Sided Spectrum**, the Nyquist frequency interval is $$\left[0,\frac{SampleRate}{2}\right]+FrequencyOffset$$ Hz.

### Frequency Vector

When you set **Frequency (Hz)** to `Auto`

, the software calculates the frequency vector for the frequency-domain input.

When you plot the two-sided spectrum by selecting **Two-Sided Spectrum** in
the **Spectrum** or **Spectrogram** tab, the frequency
vector is:

$$\left[-\frac{SampleRate}{2},\frac{SampleRate}{2}\right]$$

When you clear the **Two-Sided Spectrum**, the frequency vector is:

$$\left[0,\frac{SampleRate}{2}\right]$$

### Occupied BW

The spectrum analyzer calculates *Occupied BW* using these steps.

Calculate the total power in the measured frequency range.

Determine the lower frequency value. Starting at the lowest frequency in the range and moving upward, sum the power distributed in each frequency until the result is

$$\frac{100-OccupiedBW\%}{2}$$

of the total power.

Determine the upper frequency value. Starting at the highest frequency in the range and moving downward, sum the power distributed in each frequency until the result reaches

$$\frac{100-OccupiedBW\%}{2}$$

of the total power.

The bandwidth between the lower and upper power frequency values is the occupied bandwidth.

The frequency halfway between the lower and upper frequency values is the center frequency.

### Distortion Measurements

The spectrum analyzer calculates Distortion Measurements using these steps.

Estimate spectral content by finding peaks in the spectrum. When the algorithm detects a peak, it records the width of the peak and clears all monotonically decreasing values by treating all these values as if they belong to the peak. Using this method, the algorithm removes all spectral content centered at DC (0 Hz) from the spectrum and records the amount of bandwidth cleared (

*W*)._{0}Determine the fundamental power (

*P*) from the remaining maximum value of the displayed spectrum. Create a local estimate (_{1}*Fe*) of the fundamental frequency by computing the central moment of the power near the peak. Record the bandwidth of the fundamental power content (_{1}*W*). Then remove the power from the fundamental as in step 1._{1}Determine the power and width of the higher-order harmonics (

*P*,_{2}*W*,_{2}*P*,_{3}*W*, etc.) in succession by examining the frequencies closest to the appropriate multiple of the local estimate (_{3}*Fe*). Remove any spectral content that decreases monotonically about the harmonic frequency from the spectrum before proceeding to the next harmonic._{1}After removing the DC, fundamental, and harmonic content from the spectrum, examine the power of the remaining spectrum for its sum (

*P*), peak value (_{remaining}*P*), and median value (_{maxspur}*P*)._{estnoise}Compute the sum of all the removed bandwidth as

*W*=_{sum}*W*+_{0}*W*+_{1}*W*+...+_{2}*W*._{n}Compute the sum of powers of the second and higher-order harmonics as

*P*=_{harmonic}*P*+_{2}*P*+_{3}*P*+...+_{4}*P*._{n}Estimate the sum of the noise power as:

$${P}_{noise}=({P}_{remaining}\cdot dF+{P}_{est.noise}\cdot {W}_{sum})/RBW$$

Where

*dF*is the absolute difference between frequency bins, and*RBW*is the resolution bandwidth of the window.Then compute the metrics for THD, THD%, SINAD, SNR, and SFDR from the estimates.

$$\begin{array}{l}THD=10\cdot {\mathrm{log}}_{10}\left(\frac{{P}_{harmonic}}{{P}_{1}}\right)\\ THD\%={100.10}^{\left(THD/20\right)}\\ SINAD=10\cdot {\mathrm{log}}_{10}\left(\frac{{P}_{1}}{{P}_{harmonic}+{P}_{noise}}\right)\\ SNR=10\cdot {\mathrm{log}}_{10}\left(\frac{{P}_{1}}{{P}_{noise}}\right)\\ SFDR=10\cdot {\mathrm{log}}_{10}\left(\frac{{P}_{1}}{\mathrm{max}\left({P}_{maxspur},\mathrm{max}\left({P}_{2},{P}_{3},\mathrm{...},{P}_{n}\right)\right)}\right)\end{array}$$

### Harmonic Measurements

The harmonic distortion measurements use the spectrum trace shown in the display as the input to the measurements. The default

`Hann`

window setting of the spectrum analyzer might exhibit leakage that can completely mask the noise floor of the measured signal.The harmonic measurements attempt to correct for leakage by ignoring all frequency content that decreases monotonically away from the maximum of harmonic peaks. If the window leakage covers more than 70% of the frequency bandwidth in your spectrum, you may see a blank reading (–) reported for

**SNR**and**SINAD**. If your application can tolerate the increased equivalent noise bandwidth (ENBW), consider using a Kaiser window with a high attenuation (up to 330 dB) to minimize spectral leakage.Ignore the DC component.

After windowing, the width of each harmonic component masks the noise power in the neighborhood of the fundamental frequency and harmonics. To estimate the noise power in each region, the spectrum analyzer computes the median noise level in the nonharmonic areas of the spectrum. It then extrapolates that value into each region.

*N*^{th}order intermodulation products occur at*A***F1*+*B***F2*,where

*F1*and*F2*are the sinusoid input frequencies and |*A*| + |*B*| =*N*.*A*and*B*are integer values.For intermodulation measurements, compute the third-order intercept (TOI) point as follows.

*TOI*=_{lower}*P*+ (_{F1}*P*-_{F2}*P*)/2_{(2F1-F2)}*TOI*=_{upper}*P*+ (_{F2}*P*-_{F1}*P*)/2_{(2F2-F1)}*TOI*= + (*TOI*+_{lower}*TOI*)/2_{upper}

Where

*P*is power in decibels of the measured power referenced to 1 milliwatt (dBm).

### Averaging Method

The spectrum analyzer can calculate the moving average using two methods:

Video bandwidth — The spectrum analyzer uses a time-domain lowpass filter to smooth the noise in the signal. The video bandwidth (VBW) filter smoothes the trace and decreases noise, and the spectrum analyzer applies the filter to the data before displaying it.

Video bandwidth is the bandwidth of the lowpass filter that spectrum analyzer uses to average or smooth the noise in the signal before displaying it in the scope. The spectrum analyzer computes the video bandwidth using this equation:

$$VBW=\frac{(1-\lambda )RBW}{2\pi \lambda NENBW}$$

where,

Video bandwidth does not affect the level of the noise (noise floor), but only increases the signal-to-noise ratio and smoothes the trace of the noise. When you decrease the value of VBW, the signal-to-noise ratio improves.

The cutoff frequency of the video bandwidth filter is given by:

$${\omega}_{c}=\frac{2\pi VBW}{{F}_{s}/NFFT}$$

where

*Fs*is the input sample rate and NFFT is the number of FFT points.The spectrum analyzer shows the values of sample rate, VBW, and NFFT in the status bar at the bottom of the display. To enable, right-click the status bar and select

`Sample Rate`

,`VBW`

, and`NFFT`

.Exponential — The moving average algorithm uses the exponential weighting method to update the weights and compute the moving average recursively for each

*Z*vector that comes in by using the following recursive equations:$$\begin{array}{l}{w}_{N}=\lambda {w}_{N-1}+1\\ {\overline{z}}_{N}=\left(1-\frac{1}{{w}_{N}}\right){\overline{z}}_{N-1}+\left(\frac{1}{{w}_{N}}\right){z}_{N}\end{array}$$

λ — Forgetting factor

$${w}_{N}$$ — Weighting factor applied to the current

*Z*vector$${z}_{N}$$ — Current

*Z*vector$${\overline{z}}_{N-1}$$ — Moving average until the previous

*Z*vector$$\left(1-\frac{1}{{w}_{N}}\right){\overline{z}}_{N-1}$$ — Effect of the previous

*Z*vectors on the average$${\overline{z}}_{N}$$ — Moving average including the current

*Z*vector

## Extended Capabilities

### C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

Supports MEX code generation by treating the calls to the object as extrinsic. Does not support code generation for standalone applications.

See System Objects in MATLAB Code Generation (MATLAB Coder).

## Version History

**Introduced in R2012b**

### R2024a: `dsp.SpectrumAnalyzer`

System object warns

The `dsp.SpectrumAnalyzer`

System object warns in R2024a. Use the `spectrumAnalyzer`

object instead.

**Update Code**

The `spectrumAnalyzer`

object has the same properties as the
`dsp.SpectrumAnalyzer`

object. However, the default value of the
`Method`

property has changed to `'filter-bank'`

, and
the default value of the `AveragingMethod`

property has changed to
`'vbw'`

, which is video bandwidth.

No updates to your code are required except for:

Replacing instances of

`dsp.SpectrumAnalyzer`

with`spectrumAnalyzer`

.Updating the values of

`Method`

and`AveragingMethod`

properties, if required.

This table shows how the System object is typically used and explains how to update existing code to use the
`spectrumAnalyzer`

object.

Discouraged Usage | Recommended Replacement |
---|---|

sa = dsp.SpectrumAnalyzer dsp.SpectrumAnalyzer with properties: NumInputPorts: 1 InputDomain: 'time' SpectrumType: 'power' ViewType: 'spectrum' SampleRate: 10000 Method: 'welch' PlotAsTwoSidedSpectrum: 1 FrequencyScale: 'linear' PlotType: 'line' AxesScaling: 'auto' Show all properties |
The
To retain the same default
behavior as the sa = spectrumAnalyzer(Method="welch",... AveragingMethod="exponential") spectrumAnalyzer with properties: InputDomain: 'time' SpectrumType: 'power' ViewType: 'spectrum' SampleRate: 10000 Method: 'welch' PlotAsTwoSidedSpectrum: 1 FrequencyScale: 'linear' PlotType: 'line' AxesScaling: 'auto' Advanced FrequencyResolutionMethod: 'rbw' RBWSource: 'auto' FFTLengthSource: 'auto' FrequencySpan: 'full' OverlapPercent: 0 Window: 'hann' AveragingMethod: 'exponential' ForgettingFactor: 0.9000 SpectrumUnits: 'dBm' ReferenceLoad: 1 FrequencyOffset: 0 |

Display
spectrum data on the Spectrum Analyzer using the
swv = dsp.SineWave(Frequency=100,SampleRate=1000); swv.SamplesPerFrame = 1000; san = dsp.SpectrumAnalyzer(SampleRate=swv.SampleRate); data = []; for ii = 1:250 x = swv() + 0.05*randn(1000,1); san(x); if san.isNewDataReady data = [data;getSpectrumData(san)]; end end release(san); |
Display
spectrum data on the Spectrum Analyzer using the swv = dsp.SineWave(Frequency=100,SampleRate=1000); swv.SamplesPerFrame = 1000; san = spectrumAnalyzer(SampleRate=swv.SampleRate,... Method="welch",AveragingMethod="exponential"); data = []; for ii = 1:250 x = swv() + 0.05*randn(1000,1); san(x); if san.isNewDataReady data = [data;getSpectrumData(san)]; end end release(san); |

### R2022a: `dsp.SpectrumAnalyzer`

System object will be removed

The `dsp.SpectrumAnalyzer`

System object will be removed in a future release. Use the `spectrumAnalyzer`

object instead.

### R2022a: CCDF measurements will be removed from the `dsp.SpectrumAnalyzer`

object

The `CCDFMeasurements`

property will be removed from the `dsp.SpectrumAnalyzer`

object. If you try to edit these measurements from the
command line or from the user interface (UI), the object throws a warning message.

Use the `powermeter`

object
instead to plot and visualize the CCDF measurements.

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