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New algorithms to compute the nearness symmetric solution of the matrix equation

In this paper we consider the nearness symmetric solution of the matrix equation AXB = C to a given matrix [Formula: see text] in the sense of the Frobenius norm. By discussing equivalent form of the considered problem, we derive some necessary and sufficient conditions for the matrix [Formula: see...

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Detalles Bibliográficos
Autores principales: Peng, Zhen-yun, Fang, Yang-zhi, Xiao, Xian-wei, Du, Dan-dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937012/
https://www.ncbi.nlm.nih.gov/pubmed/27441130
http://dx.doi.org/10.1186/s40064-016-2416-x
Descripción
Sumario:In this paper we consider the nearness symmetric solution of the matrix equation AXB = C to a given matrix [Formula: see text] in the sense of the Frobenius norm. By discussing equivalent form of the considered problem, we derive some necessary and sufficient conditions for the matrix [Formula: see text] is a solution of the considered problem. Based on the idea of the alternating variable minimization with multiplier method, we propose two iterative methods to compute the solution of the considered problem, and analyze the global convergence results of the proposed algorithms. Numerical results illustrate the proposed methods are more effective than the existing two methods proposed in Peng et al. (Appl Math Comput 160:763–777, 2005) and Peng (Int J Comput Math 87: 1820–1830, 2010).