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tfrzam

Zao-Atlas-Marks time-frequency distribution

Calling Sequence

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

Parameters

X :

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

T:

a real Nt vector with elements in [1 Nx] : time instant(s) on which the TFR is evaluated (default: 1:NX).

N:

a positive integer: the number of frequency bins (default:NX).

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.

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.

TRACE :

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

'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

tfrzam computes the Zao-Atlas-Marks distribution of a discrete-time signal X, or the cross Zao-Atlas-Marks representation between two signals.

Examples

sig = fmlin(128,0.05,0.3) + fmlin(128,0.15,0.4);
g = window("kr",9,3*%pi); 
h = window("kr",27,3*%pi);
[TFR,T,F] = tfrzam(sig,1:128,128,g,h);
clf; gcf().color_map = jetcolormap(128);
Sgrayplot(T,F,TFR');

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