Smoothed Pseudo Affine Wigner time-frequency distributions.
[TFR,T,F]=tfrspaw(X) [TFR,T,F]=tfrspaw(X,T) [TFR,T,F]=tfrspaw(X,T,K) [TFR,T,F]=tfrspaw(X,T,K,NH0) [TFR,T,F]=tfrspaw(X,T,K,NH0,NG0) [TFR,T,F]=tfrspaw(X,T,K,NH0,NG0,FMIN,FMAX) [TFR,T,F]=tfrspaw(X,T,K,NH0,NG0,FMIN,FMAX,N) [TFR,T,F]=tfrspaw(X,T,K,NH0,NG0,FMIN,FMAX,N,TRACE) [TFR,T,F]=tfrspaw(...,'plot')
signal (in time) to be analyzed. If X=[X1 X2], TFRSPAW computes the cross-Smoothed Pseudo Affine Wigner distribution. (Nx=length(X)).
time instant(s) on which the TFR is evaluated (default is 1:Nx).
label of the K-Bertrand distribution. The distribution with parameterization function lambdak(u,K) = (K (exp(-u)-1)/(exp(-Ku)-1))^(1/(K-1)) is computed (default is 0).
Smoothed pseudo (active) Unterberger distribution
Smoothed pseudo Bertrand distribution
Smoothed pseudo D-Flandrin distribution
Affine smoothed pseudo Wigner-Ville distribution.
half length of the analyzing wavelet at coarsest scale. A Morlet wavelet is used. NH0 controles the frequency smoothing of the smoothed pseudo Affine Wigner distribution. (default is sqrt(Nx)).
half length of the time smoothing window.
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.
number of analyzed voices (default : automatically determined).
if nonzero, the progression of the algorithm is shown (default is 0).
if one input parameter is 'plot', tfrspwv runs tfrqview. and TFR will be plotted
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.
vector of normalized frequencies (geometrically sampled from FMIN to FMAX).
tfrspaw generates the auto- or cross- Smoothed Pseudo Affine Wigner distributions.