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Time Frequency Toolbox >> Time Frequency Toolbox > Bilinear Time-Frequency Processing in the Cohen's Class > tfrmhs

tfrmhs

Margenau-Hill-Spectrogram time-frequency distribution.

Calling Sequence

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

Parameters

X :

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

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)).

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 :

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.

F :

A N vector of normalized frequencies.

Description

tfrmhs computes the Margenau-Hill-Spectrogram distribution of a discrete-time signal X, or the cross Margenau-Hill-Spectrogram representation between two signals.

Examples

Interactive use

N=128;
sig=fmlin(N,0.1,0.4);
g=window("kr",21,3*%pi); h=window("kr",63,3*%pi); 
tfrmhs(sig,1:N,64,g,h,'plot');

Non interactive use

N=128;
sig=fmlin(N,0.1,0.4);
g=window("kr",21,3*%pi); h=window("kr",63,3*%pi); 
[TFR,T,F]=tfrmhs(sig,1:N,64,g,h);
clf;gcf().color_map= jetcolormap(128);
grayplot(T,F,TFR');

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