Abstract
We present a new algorithm for approximate joint diagonalization of several symmetric matrices. While it is based on the classical least squares criterion, a novel intrinsic scale constraint leads to a simple and easily parallelizable algorithm, called LSDIC (Least squares Diagonalization under an Intrinsic Constraint. Numerical simulations show that the algorithm behaves well as compared to other approximate joint diagonalization algorithms.
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