| Global Exponential Stability of Periodic Solution for Competitive Neural Networks with Time-Varying and Distributed Delays on Time Scales |
| Received:May 17, 2013 Revised:October 12, 2013 |
| Key Words:
stability competitive neural networks delays time scales.
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| Fund Project:Supported by the Fundamental Research Funds for the Central Universities (Grant No.JUSRP51317B) and the National Natural Science Foundation of China (Grant No.60875036). |
| Author Name | Affiliation | | Yang LIU | Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Science, Jiangnan University, Jiangsu 214122, P. R. China | | Yongqing YANG | Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Science, Jiangnan University, Jiangsu 214122, P. R. China | | Tian LIANG | Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Science, Jiangnan University, Jiangsu 214122, P. R. China | | Xianyun XU | Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Science, Jiangnan University, Jiangsu 214122, P. R. China |
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| Abstract: |
| In this paper, competitive neural networks with time-varying and distributed delays are investigated. By utilizing Lyapunov functional methods, the global exponential stability of periodic solutions of the neural networks is discussed on time scales. In addition, an example is given to illustrate the effectiveness of the theoretical results. |
| Citation: |
| DOI:10.3770/j.issn:2095-2651.2014.04.009 |
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