On Procrustes matching of non-negative matrices and an application to random tomography

We consider a Procrustes matching problem for non-negative matrices that arose in random tomography. As an alternative to the Frobenius distance, we propose an alternative non-symmetric distance using generalized inverses. Among its advantages is that it leads to a relatively simple quadratic function that can be optimized with least-square methods on manifolds.

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Accepted for publication in Linear and Multilinear Algebra, published online on 03 February 2017

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