In this paper the convergence behavior of delayed shunting inhibitory cellular neural networks with time-varying coefficients are considered. Some sufficient conditions are established to ensure that all solutions of the networks converge exponentially to the zero point, which are new and complement
New convergence behavior of high-order hopfield neural networks with time-varying coefficients
โ Scribed by Xuejun Yi; Jianying Shao; Yuehua Yu; Bing Xiao
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 145 KB
- Volume
- 219
- Category
- Article
- ISSN
- 0377-0427
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โฆ Synopsis
In this paper the convergence behavior of the delayed high-order Hopfield neural networks (HHNNs) with time-varying coefficients are considered. Some sufficient conditions are established to ensure that all solutions of the networks converge to zero point, which are new and complement of previously known results.
๐ SIMILAR VOLUMES
In this work the convergence behaviors of delayed cellular neural networks with time-varying coefficients are considered. Some sufficient conditions are established to ensure that all solutions for the networks converge exponentially to the zero point, which are new, and complement previously known
We investigate stationary oscillation for high-order Hopfield neural networks with time delays and impulses. In a recent paper [J. Zhang, Z. J. Gui, Existence and stability of periodic solutions of high-order Hopfield neural networks with impulses and delays, Journal of Computational and Applied Mat
In this paper, by utilizing the Lyapunov functionals, the analysis method and the impulsive control, we analyze the exponential stability of Hopfield neural networks with time-varying delays. A new criterion on the exponential stabilization by impulses and the exponential stabilization by periodic i