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Communication Dans Un Congrès Année : 2010

Joint Eigenvalue Decomposition Using Polar Matrix Factorization.

Laurent Albera

Résumé

In this paper we propose a new algorithm for the joint eigenvalue decomposition of a set of real non-defective matrices. Our approach resorts to a Jacobi-like procedure based on polar matrix decomposition. We introduce a new criterion in this context for the optimization of the hyperbolic matrices, giving birth to an original algorithm called JDTM. This algorithm is described in detail and a comparison study with reference algorithms is performed. Comparison results show that our approach provides quicker and more accurate results in all the considered situations.

Dates et versions

hal-00910872 , version 1 (28-11-2013)

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Xavier Luciani, Laurent Albera. Joint Eigenvalue Decomposition Using Polar Matrix Factorization.. Proceedings of the 9th International Conference Latent Variable Analysis and Signal Separation LVA/ICA 2010, Sep 2010, St. Malo, France. pp.555-562, ⟨10.1007/978-3-642-15995-4_69⟩. ⟨hal-00910872⟩
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