Title :
An iterative method for the least squares symmetric solutions of the generalized coupled Sylvester matrix equations
Author_Institution :
Coll. of Math., Chengdu Univ. of Inf. Technol., Chengdu, China
Abstract :
In this paper, an iterative method is proposed to solve the minimum Frobenius norm residual problem: min ∥AXB+CYD-E:MXN+GYH-F∥ with unknown symmetric matrices X and Y. By this method, its solutions can be obtained for any initial symmetric matrices X1 and Y1 in finite iterative steps. In addition, the least-norm solutions can also be obtained by choosing a special kind of initial symmetric matrices.
Keywords :
iterative methods; least squares approximations; matrix algebra; generalized coupled Sylvester matrix equations; initial symmetric matrices; iterative method; least squares symmetric solutions; least-norm solutions; minimum Frobenius norm residual problem; symmetric matrices; Artificial neural networks; generalized coupled Sylvester matrix equations; least squares symmetric solutions; least-norm solutions;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5620550
