Pseudo-WVD
The definition (
4.5) requires the knowledge of the quantity
from

to

, which can be a problem in practice. That is why we often
replace

in (
4.5) by a windowed version of it, leading
to the new distribution:
where

is a regular window. This
distribution is called the
pseudo Wigner-Ville distribution (noted
pseudo-WVD or PWVD in the following). This windowing operation is
equivalent to a frequency smoothing of the WVD since
where

is the Fourier transform of

. Thus, because of their
oscillating nature, the interferences will be attenuated in the pseudo-WVD
compared to the WVD. However, the consequence of this improved readability
is that many properties of the WVD are lost: the marginal properties, the
unitarity, and also the frequency-support conservation; the
frequency-widths of the auto-terms are increased by this operation.
* Example: The M-file tfrpwv.m calculates the pseudo-WVD of a signal, with the possibility to
change the length and shape of the smoothing window. If we consider a
signal composed of four gaussian atoms (obtained thanks to atoms.m), each localized at a corner of a rectangle,
>> sig=atoms(128,[32,.15,20,1;96,.15,20,1;...
32,.35,20,1;96,.35,20,1]);
and compute its WVD (see fig.
4.4)
>> tfrwv(sig);
Figure 4.4:
WVD of 4 gaussian atoms : many interferences are
present
 |
we can see the four signal terms, along with six interference terms (two of
them are superimposed). If we now compute the pseudo-WVD (see
fig.
4.5),
>> tfrpwv(sig);
Figure 4.5:
The frequency-smoothing operated by the pseudo-WVD
attenuates the interferences oscillating perpendicularly to the frequency
axis
 |
we can note the important attenuation of the interferences oscillating
perpendicularly to the frequency axis, and in return the spreading in
frequency of the signal terms.
Eric Chassande-Mottin
2005-10-26