Title :
Global asymptotic stability of a class of neural networks with distributed delays
Author :
Chen, Wu-Hua ; Zheng, Wei Xing
Author_Institution :
Coll. of Math. & Inf. Sci., Guangxi Univ.
fDate :
3/1/2006 12:00:00 AM
Abstract :
In this paper, the problem of stability analysis for a class of neural networks with distributed delays is investigated. Applying the M-matrix theory and new analysis technique, novel sufficient conditions for the existence, uniqueness, and global asymptotic stability of the equilibrium point of neural networks with distributed delays are derived. The new stability criteria can be applied to the case when the nondelayed terms cannot dominate the delayed terms, which have great significance in the design and application of neural networks with distributed delays. Three illustrative examples are presented which demonstrate the usefulness of the proposed results
Keywords :
asymptotic stability; delays; matrix algebra; neural nets; M-matrix theory; distributed delays; global asymptotic stability; neural networks; stability analysis; sufficient conditions; Artificial neural networks; Asymptotic stability; Biomedical signal processing; Integrodifferential equations; Mathematics; Neural networks; Pattern recognition; Stability analysis; Stability criteria; Sufficient conditions; Distributed delays; equilibrium point; global asymptotic stability; neural networks; time-delay systems;
Journal_Title :
Circuits and Systems I: Regular Papers, IEEE Transactions on
DOI :
10.1109/TCSI.2005.859051