www.pudn.com > tftb2002toolbox.rar > contwtgn.m

function [scalo,f,T,a,wt,wavescaled] = contwtgn(x,fmin,fmax,N,wave); 
 
% CONTWTGN      [scalo,f,T,a,wt,wavescaled] = contwtgn(x,fmin,fmax,N,wave)  
%				computes a continuous wavelet transform. 
% 
% Input: 
%	x		signal (in time) to be analyzed           
%	[fmin,fmax]  	respectively lower and upper frequency bounds of 
%           		the analysis (in cycles/sec). 
%	[N] 		number of analyzed voices 
%	[wave] 		specifies the analyzing wavelet 
%                       An order "wave" derivative of the Gaussian is chosen 
% 
% Output:     
%    scalo 		scalogram (squared magnitude of WT) 
%	 f 		frequency samples (geometrically sampled between FMAX  
%			and FMIN). 
%        T              time samples 
%	 a 		scale vector (geometrically sampled between  
%			1 and FMAX/FMIN) 
%	 wt 		coefficient 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. 
% wavescaled 		when the analyzing wavelet is Morlet or Mexican hat,  
%			wavescaled = wave. For an aritrary band-pass analyzing  
%			function, wavescaled contains columnwise the (N)  
%			scaled version of it 
% 
% Example:    	S = altes(256,0.1,0.45,10000) ; 
%             	[scalo,f,T,a,wt,wavescaled] = contwtgn(S,0.01,0.5,128,8) ; 
% 
% See also: 
% 
 
% Permission is granted for use and non-profit distribution providing that this 
% notice be clearly maintained. The right to distribute any portion for profit 
% or as part of any commercial product is specifically reserved for the author. 
 
 
% CHECK INPUT FORMATS 
 
[xr,xc] = size(x) ; 
if xr ~= 1 & xc ~= 1 
  error('1-D signals only') 
elseif xc == 1 
  x = x.' ; 
end 
 
T = 1 : length(x) ; 
 
% DEFAULT VALUES 
 
nt = size(x,2) ; 
if exist('wave') == 0  
  wave = 2 ; 
end 
 
if nargin == 1 
  XTF = fft(fftshift(x)) ; 
  sp = (abs(XTF(1:nt/2))).^2 ; 
  f = linspace(0,0.5,nt/2+1) ; f = f(1:nt/2) ; 
  plot(f,sp) ; grid ; 
  xlabel('frequency'); 
  title('Analyzed Signal Spectrum') ; 
  fmin = input('lower frequency bound = ') ; 
  fmax = input('upper frequency bound = ') ; 
  N = input('Frequency samples = ') ; 
  fmin_s = num2str(fmin) ; fmax_s = num2str(fmax) ;  
  N_s = num2str(N) ; 
  disp(['frequency runs from ',fmin_s,' to ',fmax_s,' over ',N_s,' points']) ; 
end 
if nargin == 4 | nargin == 5 
  if fmin >= fmax 
    error('fmax must be greater than fmin') ; 
  end 
end 
 
f = logspace(log10(fmax),log10(fmin),N) ; 
a = logspace(log10(1),log10(fmax/fmin),N) ; amax = max(a) ; 
 
for ptr = 1:N 
  ha = gaussn(f(ptr),wave) ; nha = (length(ha)-1)/2 ; 
  detail = conv(x,ha) ; 
  wt(ptr,:) = detail(nha+1:nha+nt) ; 
end   
 
wavescaled = wave ; 
 
 
%%%% pour etre compatible avec le format de donnees de TFTB %%%%% 
 
wt = flipud(wt) ; 
a = flipud(a(:)) ; 
f = flipud(f(:)) ; 
scalo = (wt.*conj(wt)) ; 
 
 
%%%% pour etre compatible avec le format de donnees de TFTB %%%%%