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tfrspwv

Smoothed Pseudo Wigner-Ville time-frequency distribution.

Calling Sequence

[TFR,T,F] = tfrspwv(X)
[TFR,T,F] = tfrspwv(X, T)
[TFR,T,F] = tfrspwv(X, T, N)
[TFR,T,F] = tfrspwv(X, T, N, G
[TFR,T,F] = tfrspwv(X, T, N, G, H)
[TFR,T,F] = tfrspwv(X, T, N, G, H, TRACE)
[TFR,T,F] = tfrspwv(...,'plot')

Parameters

X :

A Nx elements vector (auto-SPWV) or a Nx by 2 array signal (cross-SPWV).

T:

a real Nt vector with elements in [1 Nx] : time instant(s) (default: 1:NX).

N:

a positive integer: the number of frequency bins (default:NX). For faster computation N should be a power of 2.

G:

a real vector with odd length: the time smoothing window, (default :Hamming(N/10)).

It will be normalized such as the middle point equals 1 to preserve signal energy .

H :

real vector with odd length: the frequency smoothing window,(default: Hamming(N/4)).

It will be normalized such as the middle point equals 1 to preserve signal energy.

TRACE :

if nonzero,the progression of the algorithm is shown (default : 0).

'plot':

if the last input parameter value is 'plot', tfrqview is called and the time-frequency representation will be plotted.

TFR :

A real N by Nt array: the time-frequency representation.

F :

A N vector of normalized frequencies.

Description

computes the Smoothed Pseudo Wigner-Ville distribution of a discrete-time signal X, or the cross Smoothed Pseudo Wigner-Ville representation between two signals.

Examples

N = 128;
sig = fmlin(N,0.05,0.15) + fmlin(N,0.3,0.4);
g = window("kr",15,3*%pi);
h = window("kr",63,3*%pi);
[TFR,T,F] = tfrspwv(sig,1:N,N/2,g,h);
clf; gcf().color_map = jetcolormap(128);
Sgrayplot(T,F,TFR');

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