Zao-Atlas-Marks time-frequency distribution
[TFR,T,F] = tfrzam(X) [TFR,T,F] = tfrzam(X, T) [TFR,T,F] = tfrzam(X, T, N) [TFR,T,F] = tfrzam(X, T, N, G) [TFR,T,F] = tfrzam(X, T, N, G, H) [TFR,T,F] = tfrzam(X, T, N, G, H, TRACE) [TFR,T,F] = tfrzam(...,'plot')
A Nx elements vector (auto-ZAM) or a Nx by 2 array signal (cross-ZAM).
a real Nt vector with elements in [1 Nx] : time instant(s) on which the TFR is evaluated (default: 1:NX).
a positive integer: the number of frequency bins (default:NX).
a real vector with odd length: the time smoothing window, (default :Hamming(N/10)).
It will be normalized such as the middle point equals 1.
real vector with odd length: the frequency smoothing window,(default: Hamming(N/4)).
It will be normalized such as the middle point equals 1.
if nonzero,the progression of the algorithm is shown (default : 0).
if one input parameter is 'plot', tfrqview is called and the time-frequency representation will be plotted.
A real N by Nt array: the time-frequency representation.
A N vector of normalized frequencies.
tfrzam computes the Zao-Atlas-Marks distribution of a discrete-time signal X, or the cross Zao-Atlas-Marks representation between two signals.
sig = fmlin(128,0.05,0.3) + fmlin(128,0.15,0.4); g = window("kr",9,3*%pi); h = window("kr",27,3*%pi); [TFR,T,F] = tfrzam(sig,1:128,128,g,h); clf; gcf().color_map = jetcolormap(128); Sgrayplot(T,F,TFR'); | ![]() | ![]() |