CrossSpectrum Estimator
Estimate crosspower spectrum density
Library
Estimation / Power Spectrum Estimation
dspspect3
Description
The CrossSpectrum Estimator block outputs the frequency crosspower spectrum density of two real or complex input signals, x and y, via Welch’s method of averaged modified periodograms. The input signals must be of the same size and data type.
The CrossSpectrum Estimator block computes the current power spectrum estimate by averaging the last N power spectrum estimates, where N is the number of spectral averages defined in Number of spectral averages. The block buffers the input data into overlapping segments. You can set the length of the data segment and the amount of data overlap through the parameters set in the block dialog box. The block computes the power spectrum based on the parameters set in the block dialog box.
Each column of the input signal is treated as a separate channel. If the input is a twodimensional signal, the first dimension represents the channel length (or frame size) and the second dimension represents the number of channels. If the input is a onedimensional signal, then it is interpreted as a single channel.
Parameters
 Window length source
Source of the window length value. You can set this parameter to:
Same as input frame length
(default) — Window length is set to the frame size of the input.Specify on dialog
— Window length is the value specified in Window length.
This parameter is nontunable.
 Window length
Length of the window, in samples, used to compute the spectrum estimate, specified as a positive integer scalar greater than
2
. This parameter applies when you set Window length source toSpecify on dialog
. The default is1024
. This parameter is nontunable. Window Overlap (%)
Percentage of overlap between successive data windows, specified as a scalar in the range [
0, 100
). The default is0
. This parameter is nontunable. Averaging method
Specify the averaging method as
Running
orExponential
. In the running averaging method, the block computes an equally weighted average of a specified number of spectrum estimates defined by the Number of spectral averages parameter. In the exponential method, the block computes the average over samples weighted by an exponentially decaying forgetting factor. Number of spectral averages
Number of spectral averages, specified as a positive integer scalar. The default is
1
. The spectrum estimator computes the current power spectrum estimate by averaging the last N power spectrum estimates, where N is the number of spectral averages defined in Number of spectral averages. This parameter is nontunable.This parameter applies when Averaging method is set to
Running
. Specify forgetting factor from input port
Select this check box to specify the forgetting factor from an input port. When you do not select this check box, the forgetting factor is specified through the Forgetting factor parameter.
This parameter applies when Averaging method is set to
Exponential
. Forgetting factor
Specify the exponential weighting forgetting factor as a scalar value greater than zero and smaller than or equal to one. The default is
0.9
.This parameter applies when you set Averaging method to
Exponential
and clear the Specify forgetting factor from input port parameter. FFT length source
Source of the FFT length value. You can set this parameter to:
Auto
(default) — FFT length is set to the frame size of the input.Property
— FFT length is the value specified in FFT length.
This parameter is nontunable.
 FFT length
Length of the FFT used to compute the spectrum estimates, specified as a positive integer scalar. This parameter applies when you set FFT length source to
Property
. The default is1024
. This parameter is nontunable. Window function
Window function for the crossspectrum estimator, specified as one of
Chebyshev
Flat Top
Hamming
Hann
Kaiser
Rectangular
. The default isHann
. This parameter is nontunable. Sidelobe attenuation of window (dB)
Side lobe attenuation of the window, specified as real positive scalar. This parameter applies when you set Window function to
Chebyshev
orKaiser
. The default is60
. This parameter is nontunable. Frequency range
Frequency range of the crossspectrum estimator. You can set this parameter to:
centered
(default) — The crossspectrum estimator computes the centered twosided spectrum of complex or real input signals, x and y. The length of the crossspectrum estimate is equal to the FFT length. The spectrum estimate is computed over the frequency range[SampleRate/2 SampleRate/2]
when the FFT length is even and[SampleRate/2 SampleRate/2]
when FFT length is odd.onesided
— The crossspectrum estimator computes the onesided spectrum of real input signals, x and y. When the FFT length, NFFT is even, length of the crossspectrum estimate is (NFFT/2
) +1
, and is computed over the frequency range[0 SampleRate/2]
. When the FFT length, NFFT is odd, length of the crossspectrum estimate is (NFFT + 1)/2
, and is computed over the frequency range[0 SampleRate/2]
.twosided
— The crossspectrum estimator computes the twosided spectrum of complex or real input signals, x and y. The length of the crossspectrum estimate is equal to the FFT length. The spectrum estimate is computed over the frequency range[0 SampleRate]
, whereSampleRate
is the sample rate of the input signal.
This parameter is nontunable.
 Inherit sample rate from input
When you select this check box, the block’s sample rate is computed as N/Ts, where N is the frame size of the input signal, and Ts is the sample time of the input signal. When you clear this check box, the block sample rate is the value specified in Sample rate (Hz). By default, this check box is selected.
 Sample rate (Hz)
Sample rate of the input signal, specified as a positive scalar value. The default is
44100
. This parameter applies when you clear the Inherit sample rate from input check box. This parameter is nontunable. Simulate using
Type of simulation to run. You can set this parameter to:
Interpreted execution
(default)Simulate model using the MATLAB^{®} interpreter. This option shortens startup time.
Code generation
Simulate model using generated C code. The first time you run a simulation, Simulink^{®} generates C code for the block. The C code is reused for subsequent simulations, as long as the model does not change. This option requires additional startup time but provides faster subsequent simulations.
Supported Data Types
Port  Supported Data Types 

Input 

Output 

Algorithms
References
[1] Hayes, Monson H. Statistical Digital Signal Processing and Modeling. Hoboken, NJ: John Wiley & Sons, 1996.
[2] Kay, Steven M. Modern Spectral Estimation: Theory and Application. Englewood Cliffs, NJ: Prentice Hall, 1999.
[3] Stoica, Petre, and Randolph L. Moses. Spectral Analysis of Signals. Englewood Cliffs, NJ: Prentice Hall, 2005.
[4] Welch, P. D. ''The Use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time Averaging Over Short Modified Periodograms''. IEEE Transactions on Audio and Electroacoustics. Vol. 15, No. 2, June 1967, pp. 70–73.