Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1893405 | Chaos, Solitons & Fractals | 2009 | 9 Pages |
Abstract
For bidirectional associate memory neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov functional method and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. A numerical example is given to demonstrate the effectiveness of the obtained results.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Statistical and Nonlinear Physics
Authors
Ju H. Park, S.M. Lee, O.M. Kwon,