Wigner-Ville distribution and smoothed pseudo Wigner-Ville distribution

`d = wvd(x)`

`d = wvd(x,fs)`

`d = wvd(x,ts)`

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

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

`d = wvd(___,'smoothedPseudo',Name,Value)`

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

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

`wvd(___)`

specifies additional options for the smoothed pseudo Wigner-Ville distribution using
name-value pair arguments. You can specify `d`

= wvd(___,'smoothedPseudo',`Name,Value`

)`twin`

and
`fwin`

in this syntax, or you can omit them.

`wvd(___)`

with no output arguments plots the
Wigner-Ville or 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] O'Toole, John M., and Boualem
Boashash. "Fast and memory-efficient algorithms for computing quadratic time-frequency
distributions." *Applied and Computational Harmonic Analysis*. Vol. 35,
No. 2, pp. 350–358.