<< tfrrspwv Reassigned Time-Frequency Processing Choice of Particular Signals >>

stftb >> stftb > Reassigned Time-Frequency Processing > tfrrstan

tfrrstan

Reassigned Stankovic distribution

Calling Sequence

[TFR,RTFR,HAT] = tfrrstan(X)
[TFR,RTFR,HAT] = tfrrstan(X, T)
[TFR,RTFR,HAT] = tfrrstan(X, T, N)
[TFR,RTFR,HAT] = tfrrstan(X, T, N, G)

[TFR,RTFR,HAT] = tfrrstan(X, T, N, G, H)
[TFR,RTFR,HAT] = tfrrstan(X, T, N, G, H, TRACE)
[TFR,RTFR,HAT] = tfrrstan(...,'plot')

Parameters

X :

A Nx elements vector: the analyzed signal .

T:

a real Nt vector with elements regularly spaced 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 frequency averaging window (default :[0.25 0.5 0.25]).

H :

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

TRACE :

A boolean (or a real scalar) if true (or nonzero),the progression of the algorithm is shown (default : %f).

'plot':

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

TFR :

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

RTFR :

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

HAT :

A complex N by Nt array: the reassignment vectors.

Description

tfrrstan computes the Stankovic distribution and its reassigned version.

Examples

N = 128;
sig = fmlin(N,0.1,0.4);
g = window('hn',9); 
h = window("hn",61); 
t = 1:2:128;
tfr = tfrrstan(sig,t,N,g,h);
f = (0.5*(0:N-1)/N)';
clf; gcf().color_map = jetcolormap(128);
grayplot(t,f,tfr');

Authors


Report an issue
<< tfrrspwv Reassigned Time-Frequency Processing Choice of Particular Signals >>