Title
New sufficient conditions for absolute stability of neural networks
Document Type
Article
Publication Date
12-1-1998
Abstract
The main result obtained in this paper is that for a neural network with interconnection matrix T, if -T is quasi-diagonally rowsum or column-sum dominant, then the network system is absolutely stable. The above two sufficient conditions for absolute stability are independent of the existing sufficient ones in the literature. Under either of the above two sufficient conditions for absolute stability, the vector field defined by the network system is also structurally stable. © 1998 IEEE.
Publication Source (Journal or Book title)
IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
First Page
584
Last Page
586
Recommended Citation
Liang, X., & Wu, L. (1998). New sufficient conditions for absolute stability of neural networks. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 45 (5), 584-586. https://doi.org/10.1109/81.668873