Title

Absolute exponential stability of neural networks with asymmetric connection matrices

Document Type

Article

Publication Date

1-1-1997

Abstract

In this letter, the absolute exponential stability result of neural networks with asymmetric connection matrices is obtained, which generalizes the existing one about absolute stability of neural networks, by a new proof approach. It is demonstrated that the network time constant is inversely proportional to the global exponential convergence rate of the network trajectories to the unique equilibrium. A numerical simulation example is also given to illustrate the obtained analysis results.

Publication Source (Journal or Book title)

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

First Page

1531

Last Page

1533

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