The cross-covariance matrix is a statistical tool that captures the covariance between two different random vectors (or random variables). Specifically, it quantifies how much two random variables change together. Unlike the covariance matrix, which involves the variances of a single random vector, the cross-covariance matrix deals with the relationships between different vectors.
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