performs one of the matrix-vector operations y := alpha*A*x + beta*y, or y := alpha*A *x + beta*y, where alpha and beta are scalars, x and y are vectors and A is an
m by n matrix
function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag)
％CUM2X Cross-covariance
％ y_cum = cum2x (x,y,maxlag, samp_seg, overlap, flag)
％ x,y - data vectors/matrices with identical dimensions
％ if x,y are matrices, rather than vectors, columns are
％ assumed to correspond to independent realizations,
％ overlap is set to 0, and samp_seg to the row dimension.
％ maxlag - maximum lag to be computed [default = 0]
％ samp_seg - samples per segment [default = data_length]
％ overlap - percentage overlap of segments [default = 0]
％ overlap is clipped to the allowed range of [0,99].
