f_getcorr.m

digital signal processing常用工具箱

function [x,y,L,M,user,fs,xm,xm_old] = f_getcorr (xm,xm_old,L,M,L_max,c,d,x,y,user,fs,hc_type);

%F_GETCORR: Compute inputs for GUI module G_CORRELATE
%
% Usage:       [x,y,L,M,user,fs] = f_getcorr (xm,L,M,L_max,c,d,x,y,user,fs);
%
% Inputs: 
%         xm      = type of input (1 to 6)
%
%                   1 = white noise
%                   2 = periodic 
%                   3 = impulse train 
%                   4 = recorded x and y
%                   5 = user defined
%
%         xm_old  = previous xm  
%         L       = number of samples of x
%         M       = number of samples of y (M <= L)
%         L_max   = maximum number of samples of x
%         c       = scale factor for y
%         d       = delay for y
%         x       = current signal x
%         y       = current signal y 
%         user    = string containing default name of MAT-file with
%                   user data x,y,fs
%         fs      = sampling frequency of x and y
%         hc_type = array of handles to input type radio buttons 
% Outputs: 
%          x      = L by 1 vector containing first input signal
%          y      = M by 1 vector containing second input signal
%          L      = number of samples of x
%          M      = number of samples of y (M <= L)
%          user   = string containing default name of MAT-file with
%                   user data x,y,T
%          fs     = sampling frequency of x and y
%          xm     = type of input
%          xm_old = previous value of xm
%
% Note:  When xm <= 2, x(k) = v(k) + a*y(k-d)  

% Initialize

M = min(M,L);

% Construct signals

switch (xm)
   
case 1,                                          % white noise
   
   x = -1 + 2*rand(L,1);
   y = -1 + 2*rand(M,1);
   for i = 1 : M
      k = i + d;
      if k <= L
         x(k) = x(k) + c*y(k-d);
      end
   end
   
case 2,                                          % periodic

   rand ('seed',3000)
   c = 0.5;
   x = f_randu(L,1,-c,c);
   for i = 1 : 5
      b = f_randu(1,1,0,1);
      phi = f_randu(1,1,pi,pi);
      for k = 1 : L
         x(k) = x(k) + b*cos(60*pi*i*k/L + phi);
      end
   end
   y = f_randu(M,1,0,0);
   for i = 1 : 5
      b = f_randu (1,1,0,1);
      phi = f_randu(1,1,pi,pi);
      for k = 1 : M
         y(k) = y(k) + b*cos(30*pi*i*k/M + phi);
      end
   end
   for i = 1 : M
      k = i + d;
      if k <= L
         x(k) = x(k) + c*y(k-d);
     end
   end
      
case 3,                                          % impulse train
   
   rand ('seed',2000)
   c = 0.3;
   x = f_randu(L,1,-c,c);
   m = floor(L/8);
   for i = 1 : 5
      b = f_randu(1,1,0,1);
      phi = f_randu (1,1,-pi,pi);
      for k = 1 : L
         x(k) = x(k) + b*cos(16*pi*i*k/L + phi);
      end
   end
   y = zeros(M,1);
   for i = 1 : M
       if mod(i-1,m) == 0
           y(i) = 1;
       end
   end
   
case 4,                                          % record x

   [x,L,xm_x,fs] = f_record (x,L,2.0,fs,xm,xm_old,hc_type);
   beep
   [y,M,xm,fs] = f_record (y,M,0.5,fs,xm,xm_old,hc_type);
   xm = xm_x;    
        
case 5,                                          % user defined
   
   caption = 'Select MAT-file containing x,y,fs';
   [user1,path] = f_getmatfile (caption,user);
   if user1 ~= 0
       user = user1;
       old_path = pwd;
       cd (path);
       load (user,'x','y','fs')
       cd (old_path)
       nx = length(x);
       ny = length(y);
       if ny > nx
           y(nx+1:ny) = [];
       end
   else
       set (hc_type(xm),'Value',0);
       set (hc_type(xm_old),'Value',1);
       xm = xm_old;
   end

end

% Check x and y

xm_old = xm;
x = f_tocol(x);
y = f_tocol(y);
L = length(x);
if L > L_max
    x(L_max+1:L) = [];
    L = L_max;
end
M = length(y);
if M > L
   y(L+1:M) = []; 
   M = L;
end