Note: This page has been translated by MathWorks. Click here to see

To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

Cross Wigner-Ville distribution and cross smoothed pseudo Wigner-Ville distribution

`d = xwvd(x,y)`

`d = xwvd(x,y,fs)`

`d = xwvd(x,y,ts)`

`d = xwvd(___,'smoothedPseudo')`

`d = xwvd(___,'smoothedPseudo',twin,fwin)`

`d = xwvd(___,'smoothedPseudo','NumFrequencyPoints',nf)`

`d = xwvd(___,'MinThreshold',thresh)`

`[d,f,t] = xwvd(___)`

`xwvd(___)`

returns the cross smoothed pseudo Wigner-Ville distribution of `d`

= xwvd(___,'smoothedPseudo')`x`

and
`y`

. The function uses the length of the input signals to choose the
lengths of the windows used for time and frequency smoothing. This syntax can include any
combination of input arguments from previous syntaxes.

`xwvd(___)`

with no output arguments plots the real
part of the cross Wigner-Ville or cross smoothed pseudo Wigner-Ville distribution in the
current figure.

[1] Cohen, Leon.
*Time-Frequency Analysis: Theory and Applications*. Englewood Cliffs,
NJ: Prentice-Hall, 1995.

[2] Mallat, Stéphane. *A
Wavelet Tour of Signal Processing*. Second Edition. San Diego, CA: Academic
Press, 1999.

[3] Malnar, Damir, Victor Sucic, and
Boualem Boashash. "A cross-terms geometry based method for components instantaneous frequency
estimation using the cross Wigner-Ville distribution." In *11th International
Conference on Information Sciences, Signal Processing and their Applications
(ISSPA)*, pp. 1217–1222. Montréal: IEEE^{®}, 2012.