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Exponential Stability Analysis of Cohen-Grossberg Neural Networks with Time-varying Delays 被引量:1

Exponential Stability Analysis of Cohen-Grossberg Neural Networks with Time-varying Delays
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摘要 In this paper, we study Cohen-Grossberg neural networks (CGNN) with time-varying delay. Based on Halanay inequality and continuation theorem of the coincidence degree, we obtain some sufficient conditions ensuring the existence, uniqueness, and global exponential stability of periodic solution. Our results complement previously known results. In this paper, we study Cohen-Grossberg neural networks (CGNN) with time-varying delay. Based on Halanay inequality and continuation theorem of the coincidence degree, we obtain some sufficient conditions ensuring the existence, uniqueness, and global exponential stability of periodic solution. Our results complement previously known results.
出处 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2012年第1期181-192,共12页 应用数学学报(英文版)
基金 Supported by the National Natural Science Foundation of China (No. 11071060) Key Program of Application Science Foundation of Hunan Province (No. 2008FJ2008)
关键词 neural network exponential stability periodic solution DELAY neural network, exponential stability, periodic solution, delay
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