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A centroid (Karcher mean) approach to the joint approximate diagonalisation problem: The real symmetric case

机译:重心对角化问题的质心(Karcher均值)方法:实对称情况

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摘要

A real symmetric matrix is diagonalisable by a suitable orthonormal change of basis. The joint approximate diagonalisation problem is to find an orthonormal change of basis which simultaneously diagonalises, or approximately diagonalises, two or more real symmetric matrices. A number of important signal processing problems require the computation of a joint approximate diagonaliser. However, no algorithm to date is guaranteed to find the optimal diagonaliser. This paper reformulates the diagonalisation problem as a convex optimisation problem on a Riemannian manifold and is thus able to guarantee global convergence to the optimal diagonaliser. (C) 2005 Elsevier Inc. All rights reserved.
机译:实对称矩阵可通过适当的正交正交变化对角线化。联合近似对角化问题是找到一个基数的正交变化,该变化同时对角化或近似对角化两个或多个实对称矩阵。许多重要的信号处理问题都需要计算联合近似对角化器。但是,迄今为止,尚无算法可以保证找到最佳对角化器。本文将对角化问题重新公式化为黎曼流形上的凸优化问题,因此能够保证全局收敛到最优对角化器。 (C)2005 Elsevier Inc.保留所有权利。

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