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Time Frequency Toolbox >> Time Frequency Toolbox > Bilinear Time-Frequency Processing in the Affine Class > tfrscalo

tfrscalo

Scalogram, for Morlet or Mexican hat wavelet.

Calling Sequence

[TFR,T,F,WT]=tfrscalo(X)
[TFR,T,F,WT]=tfrscalo(X,T)
[TFR,T,F,WT]=tfrscalo(X,T,WAVE,FMIN, FMAX)
[TFR,T,F,WT]=tfrscalo(X,T,WAVE,FMIN,FMAX,N)
[TFR,T,F,WT]=tfrscalo(X,T,WAVE,FMIN,FMAX,N,TRACE)
[TFR,T,F,WT]=tfrscalo(...,'plot')

Description

tfrscalo computes the scalogram (squared magnitude of a continuous wavelet transform).

Parameters

X :

signal (in time) to be analyzed (Nx=length(X)). Its analytic version is used (z=hilbert(real(X))).

T :

time instant(s) on which the TFR is evaluated (default : 1:Nx).

WAVE :

half length of the Morlet analyzing wavelet at coarsest scale. If WAVE = 0, the Mexican hat is used. WAVE can also be a vector containing the time samples of any bandpass function, at any scale. (default : sqrt(Nx)).

FMIN,FMAX :

respectively lower and upper frequency bounds of the analyzed signal. These parameters fix the equivalent frequency bandwidth (expressed in Hz). When unspecified, you have to enter them at the command line from the plot of the spectrum. FMIN and FMAX must be >0 and <=0.5.

N :

number of analyzed voices.

TRACE :

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

'plot':

if one input parameter is 'plot', tfrscalo runs tfrqview. and TFR will be plotted

TFR :

time-frequency matrix containing the coefficients of the decomposition (abscissa correspond to uniformly sampled time, and ordinates correspond to a geometrically sampled frequency). First row of TFR corresponds to the lowest frequency.

F :

vector of normalized frequencies (geometrically sampled from FMIN to FMAX).

WT :

Complex matrix containing the corresponding wavelet transform. The scalogram TFR is the square modulus of WT.

Examples

sig=altes(64,0.1,0.45); tfrscalo(sig,'plot');

Authors

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