# Spectral Analysis

The frequency-domain representation of a signal reveals important
signal characteristics that are difficult to analyze in the time domain.
Spectral analysis lets you characterize the frequency content of a
signal. Perform real-time spectral analysis of a dynamic signal using
the `spectrumAnalyzer`

object in MATLAB^{®} and the Spectrum Analyzer block in
Simulink^{®}. The Spectrum Analyzer uses the filter bank method or the
Welch's method of averaging modified periodogram to compute the spectral
data. Both these methods are FFT-based spectral estimation methods that
make no assumptions about the input data and can be used with any kind
of signal. For more information on the algorithm the Spectrum Analyzer
uses, see Spectral Analysis. In addition
to viewing the spectrum, you can also view the spectrogram of the signal
in the Spectrum Analyzer. For an example, see View the Spectrogram Using Spectrum Analyzer.

If you want to acquire this data for post processing in MATLAB, call `isNewDataReady`

and `getSpectrumData`

object functions on the Spectrum
Analyzer object. By calling these functions in the streaming loop, you
can acquire the entire spectral data. In Simulink, to acquire the spectral data, create a `SpectrumAnalyzerBlockConfiguration`

object and run the
`getSpectrumData`

function on this object. Note that in
Simulink, you can acquire only the last frame of the spectral data
shown on the Spectrum Analyzer.

Alternately, you can use the `dsp.SpectrumEstimator`

System object™ and Spectrum Estimator block to
compute the power spectrum and acquire the spectral data for further
processing. To view the spectral data computed by the spectrum
estimator, use an array plot. For examples, see Estimate the Power Spectrum in MATLAB and Estimate the Power Spectrum in Simulink.

## Objects

## Blocks

## Topics

**Spectral Analysis**Spectral analysis is the process of estimating the power spectrum (PS) of a signal from its time-domain representation.

**Estimate the Power Spectrum in MATLAB**Compute the power spectrum using the

`spectrumAnalyzer`

and the`dsp.SpectrumEstimator`

objects.**Estimate the Power Spectrum in Simulink**Compute the power spectrum using the Spectrum Analyzer and the Spectrum Estimator blocks.

**Streaming Power Spectrum Estimation Using Welch's Method**Use Welch's method of averaged modified periodogram to estimate power spectrum.

**High Resolution Filter-Bank-Based Power Spectrum Estimation**This example shows how to perform high resolution spectral analysis by using an efficient polyphase filter bank sometimes referred to as a channelizer.

**View the Spectrogram Using Spectrum Analyzer**Spectrograms are a two-dimensional representation of the power spectrum of a signal as this signal sweeps through time.

**Estimate the Transfer Function of an Unknown System**You can estimate the transfer function of an unknown system based on the system's measured input and output data.

**Continuous-Time Transfer Function Estimation**This example shows how to use the Discrete Transfer Function Estimator block to estimate the magnitude and phase response of a continuous-time analog filter.

**Group Delay Estimation in Simulink**This example shows how to estimate the group delay of a filter in Simulink®.

**Variable-Size Signal Support DSP System Objects**List of System objects that support variable-sized signals in DSP System Toolbox™.