Calculate windowed cross correlation between two signals.
c = corrgram(a,b,maxlag,window,noverlap,method) [c,l,t] = corrgram(...) c = corrgram(a,b) corrgram(a,b)
c = corrgram(a,b,maxlag,window,noverlap) calculates the windowed cross correlation between the signals in vector a and vector b. corrgram splits the signals into overlapping segments and forms the columns of c with their cross correlation values up to maximum lag specified by scalar maxlag. Each column of c contains the cross correlation function between the short-term, time-localized signals a and b. Time increases linearly across the columns of c, from left to right. Lag increases linearly down the rows, starting at -maxlag. If lengths of a and b differ, the shorter signal is filled with zeros. If n is the length of the signals, c is a matrix with 2*maxlag+1 rows and k = fix((n-noverlap)/(window-noverlap)) columns.
c = corrgram(...,method) using either Pearson correlation ('pearson', default), Spearman's rank correlation ('spearman'), or Kendall's Tau ('kendall').
[c,l,t] = corrgram(...) returns a column of lag L and one of time T at which the correlation coefficients are computed. L has length equal to the number of rows of c, T has length k.
c = corrgram(a,b) calculates windowed cross correlation using defeault settings; the defeaults are maxlag = floor(0.1n), window = floor(0.1*n) and noverlap = 0. You can tell corrgram to use the defeault for any parameter by leaving it off or using  for that parameter, e.g. corrgram(a,b,,1000).
corrgram(a,b) with no output arguments plots the windowed cross correlation using the current figure.
x = cos(0:.01:10*pi)'; y = sin(0:.01:10*pi)' + .5 * randn(length(x),1); corrgram(x,y)