Unitary Bertrand time-frequency distribution.
[TFR,T,F] = tfrbert(X) [TFR,T,F] = tfrbert(X, T) [TFR,T,F] = tfrbert(X, T, FMIN,FMAX) [TFR,T,F] = tfrbert(X, T, FMIN,FMAX, N) [TFR,T,F] = tfrbert(X, T, FMIN,FMAX, N, TRACE) [TFR,T,F] = tfrbert(...,'plot')
It can be:
a vector of size Nx: the signal (in time)to be analyzed .
or a 2 by Nx matrix for the cross-unitary Bertrand distribution)
a real vector: the time instant(s) on which the TFR is evaluated (default : 1:Nx).
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 : 0).
if one input parameter is 'plot', tfrbert runs tfrqview. and TFR will be plotted
time-frequency matrix containing the coefficients of the distribution (x-coordinate corresponds to uniformly sampled time, and y-coordinate corresponds to a geometrically sampled frequency). First row of TFR corresponds to the lowest frequency.
vector of normalized frequencies (geometrically sampled from FMIN to FMAX).
tfrbert generates the auto- or cross- unitary Bertrand distribution.
Interactive use
Non interactive use
N = 128; sig = altes(N,0.1,0.45); T = 1:N; [tfr,t,f] = tfrbert(sig,T,0.1,0.35,64); clf; gcf().color_map = jetcolormap(128); grayplot(t,f,tfr'); | ![]() | ![]() |