rows = 32;   %number of output samples from compression matrix
cols = 2048;  %number of input samples supplied to compression matrix
matrixA = randn(rows, cols) + 1i*randn(rows, cols);
matrixB = randn(rows, cols)+ 1i*randn(rows, cols);

%compute all possible cross-correlations
xc = abs(matrixA * matrixB');
%find the maximum
result = max(max(abs(matrixA * matrixB')));
%todo:  scale by sqrt(n)
%...