computes a continuous wavelet transform
[scalo,f,T,a,wt,wavescaled] = contwtgn(x, fmin, fmax, N, wave)
a real vector of size Nx: the signal (in time) to be analyzed
a positive scalar in ]0 0.5], the normalized lower frequency bound in (in Hz) of the analyzed signal. When unspecified, you have to enter it at the command line from the plot of the spectrum.
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.
a positive integer: number of analyzed voices. When unspecified, you have to enter it at the command line.
a positive integer: the analyzing wavelet order "wave" derivative of the Gaussian is chosen
a real N by Nx matrix: the scalogram (squared magnitude of WT)
a real column vector of size N: the frequency samples (geometrically sampled between fmax and fmin).
a real row vector of size Nx: the time samples (sampling period =1)
a real column vector of size N: the scale vector (geometrically sampled between 1 and fmax/fmin)
a real N by Nx matrix: the coefficients of the wavelet transform. X-axis corresponds to time (uniformly sampled), Y-axis corresponds to frequency (or scale) samples (geometrically sampled between fmin (resp. fmax/fmin and fmax (resp. 1) First row of wt corresponds to the lowest analyzed frequency.
when the analyzing wavelet is Morlet or Mexican hat, wavescaled = wave.
contwtgn computes a continuous wavelet transform.
S = altes(256,0.1,0.45,10000) ; [scalo,f,T] = contwtgn(S,0.01,0.5,128,8) ; clf; gcf().color_map= jetcolormap(128); grayplot(T,f,scalo') | ![]() | ![]() |