I'm trying to understand the Wiener Filter, and I have a few questions. 1. How can there be such a thing as a correlation matrix of 1 vector. I read here: R_yy = E[ y(k) * y^T(k) ] where y(k) is a vector, and y_T(x) is the same vector transposed. I thought correlation represents the degree of correspondence between 2 variables, so how can we say there is a correlation between 2 equivalent vectors? 2. They present a matrix R_yy as the correlation matrix (mentioned above). Then they say vector "r_yy" is the first column of R_yy. If that is so, what are the other columns of R_yy? 3. The book first presents the Wiener filter formulation by saying that in minimizing the MSE criterion, we can find "h_w" (the wiener filter vector). They go on to another form of the Wiener filter by saying: h_w = h_1 - inv(R_yy)*r_vv where h_1 was defined as [1 0 0 0 ...]^T and r_vv, I suppose is the correlation (once again I dont know how one can have correlation between 2 equivalent vectors). Thank you for any help.