<< tfrdfla Bilinear Time-Frequency Processing in the Affine Class tfrspaw >>

stftb >> stftb > 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 :

a real Nt vector with elements in [1 Nx] : time instant(s) on wich the tfr is computed. (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:

a positive scalar in ]0 0.5], the normalized lower frequency bound in (Hz) of the analyzed signal. When unspecified, you have to enter it at the command line from the plot of the spectrum.

FMAX :

a positive scalar in ]0 0.5], the normalized upper frequency bound (in Hz) of the analyzed signal. When unspecified, you have to enter it at the command line from the plot of the spectrum.

N :

positive integer: number of analyzed voices. When unspecified, you have to enter it at the command line from the plot of the spectrum.

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 :

N by Nt real array: the 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 :

N by Nt complex array containing the corresponding wavelet transform. The scalogram TFR is the square modulus of WT multiplied by a constant factor.

Examples

Interactive use

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

Non-interactive use

N = 128;
sig = altes(N,0.1,0.45); 
T = 1:N;
wave = sqrt(N);
[fmin, fmax] = (0.1, 0.35);
[tfr,t,f,wt] = tfrscalo(sig,T,wave,fmin,fmax,128);
clf; gcf().color_map = jetcolormap(128);
grayplot(t,f,tfr');

Authors


Report an issue
<< tfrdfla Bilinear Time-Frequency Processing in the Affine Class tfrspaw >>