Another neural network based approach for computing eigenvalues and eigenvectors of real skew-symmetric matrices

✍ Scribed by Ying Tang; Jianping Li

• Publisher: Elsevier Science
• Year: 2010
• Tongue: English
• Weight: 390 KB
• Volume: 60
• Category: Article
• ISSN: 0898-1221
• DOI: 10.1016/j.camwa.2010.06.020

✦ Synopsis

This paper introduces a novel neural network based approach for extracting the eigenvalues with the largest or smallest modulus of real skew-symmetric matrices, as well as the corresponding eigenvectors. To this end, unlike the previous neural network based methods that can be summarized by some 2n-dimensional ordinary differential equations (ODEs), where n is the order of the given skew-symmetric matrix, our proposed approach corresponds to an ODE of order n, instead of 2n. Hence, the scale of networks can be reduced a lot. Simulations verify the computational capability of such approach.