Title
A simple proof of a necessary and sufficient condition for absolute stability of symmetric neural networks
Document Type
Article
Publication Date
12-1-1998
Abstract
The main result that for a neural circuit of the Hopfield type with a symmetric connection matrix T, the negative semideflniteness of T is a necessary and sufficient condition for absolute stability was obtained and proved by rather complex procedures by Forti et al. This brief gives a very simple proof of this result, using only the well-known total stability result about Hopfield type neural circuits with a symmetric connection matrix and the basic algebraic properties of real symmetric matrices. © 1998 IEEE.
Publication Source (Journal or Book title)
IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
First Page
1010
Last Page
1011
Recommended Citation
Liang, X., & Wu, L. (1998). A simple proof of a necessary and sufficient condition for absolute stability of symmetric neural networks. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 45 (9), 1010-1011. https://doi.org/10.1109/81.721271