Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1865330 | Physics Letters A | 2006 | 13 Pages |
Abstract
This Letter provides new exponential stability criteria for discrete-time neural networks with variable delays. The main technique is to reduce exponential convergence estimation of the neural network solution to that of one component of the corresponding solution by constructing Lyapunov function based on M-matrix. By introducing the tuning parameter diagonal matrix, the delay-independent and delay-dependent exponential stability conditions have been unified in the same mathematical formula. The effectiveness of the new results are illustrated by three examples.
Keywords
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Physical Sciences and Engineering
Physics and Astronomy
Physics and Astronomy (General)
Authors
Wu-Hua Chen, Xiaomei Lu, Dong-Ying Liang,