Abstract:We consider estimating the covariance matrix from two data sets, one whose covariance matrix R 1 is the sought one and another set of samples whose covariance matrix R 2 slightly differs from the sought one, due e.g. to different measurement configurations. We assume however that the two matrices are rather close, which we formulate by assuming that R 1 / 2 1 R −1 2 R 1 / 2 1 | R 1 follows a Wishart distribution around the identity matrix. It turns out that this assumption results in two data sets with differe…

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