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Measurements and Statistics

Bistate waveform measurements, variance, histogram, autocorrelation

You can use DSP System Toolbox™ blocks and System objects to measure the moving statistics and stationary statistics of signals in MATLAB® and Simulink®. Moving statistics refer to the statistics of streaming signals that change with time. In the sliding window method for computing moving statistics, a window of specified length moves over the data sample by sample as the new data comes in. The objects and blocks compute the statistics of the data within this window. The exponential weighting method applies a set of weights to the data samples and processes the weighted data. These weights are computed recursively based on the age of the data. For stationary statistics, the blocks and objects compute the statistics of all the data that is available in a batch.

In addition to measuring statistics, you can also measure the histogram, pulse metrics, and transition metrics of signals by using the dsp.Histogram, dsp.PulseMetrics, and dsp.TransitionMetrics System objects.

System Objects

dsp.MedianFilterMedian filter
dsp.MovingAverageMoving average
dsp.MovingMaximumMoving maximum
dsp.MovingMinimumMoving minimum
dsp.MovingRMSMoving Root Mean Square
dsp.MovingStandardDeviationMoving standard deviation
dsp.MovingVarianceMoving variance
dsp.AutocorrelatorAutocorrelation sequence
dsp.CrosscorrelatorCross-correlation of two inputs
dsp.MaximumFind maximum value of input or sequence of inputs
dsp.MeanFind mean value of input or sequence of inputs
dsp.MedianMedian value of input
dsp.MinimumFind minimum values of input or sequence of inputs
dsp.RMSRoot mean square of vector elements
dsp.StandardDeviationStandard deviation of input or sequence of inputs
dsp.VarianceVariance of input or sequence of inputs
dsp.HistogramHistogram of input or sequence of inputs
dsp.PeakToPeakPeak-to-peak value
dsp.PeakToRMSPeak-to-root-mean-square value of vector
dsp.PulseMetricsPulse metrics of bilevel waveforms
dsp.StateLevelsState-level estimation for bilevel rectangular waveform
dsp.TransitionMetricsTransition metrics of bilevel waveforms

Blocks

Median FilterMedian filter
Moving AverageMoving average
Moving MaximumMoving maximum
Moving MinimumMoving minimum
Moving RMSMoving RMS
Moving Standard DeviationMoving standard deviation
Moving VarianceMoving variance
AutocorrelationAutocorrelation of N-D array
CorrelationCross-correlation of two N-D arrays
MaximumMaximum values of input or sequence of inputs
MeanFind mean value of input or sequence of inputs
MedianMedian value of input
MinimumMinimum values of input or sequence of inputs
RMSRoot mean square value of input or sequence of inputs
SortSort input elements by value
Standard DeviationStandard deviation of input or sequence of inputs
VarianceVariance of input or sequence of inputs
HistogramHistogram of input or sequence of inputs

Concepts

What Are Moving Statistics?

Learn how moving statistics are calculated.

Sliding Window Method and Exponential Weighting Method

Learn the differences between the sliding window method and exponential weighting method.

How Is a Moving Average Filter Different from an FIR Filter?

Moving average filter is a special case of the FIR filter.

Signal Statistics

This example shows how to perform statistical measurements on an input data stream using DSP System Toolbox™ functionality available at the MATLAB® command line.

Measure Statistics of Streaming Signals

Compute the moving average of streaming signals using MATLAB functions and System objects.

Remove High-Frequency Noise from Gyroscope Data

Remove high-frequency noise using a median filter.

Energy Detection in the Time Domain

Detect the event when the signal energy crosses a particular threshold value.

Measure Pulse and Transition Characteristics of Streaming Signals

Learn how to compute the basic pulse and transition metrics of streaming signals.

Variable-Size Signal Support DSP System Objects

List of System objects which support variable-sized signals in DSP System Toolbox.

Featured Examples

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