期刊
NEUROCOMPUTING
卷 251, 期 -, 页码 81-89出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2017.04.013
关键词
Complex-valued neural networks; Global stability; Time-delay
资金
- National Natural Science Foundation of China [61473178, 61503222, 61673227]
- NSERC, Canada
- Research Fund for the Taishan Scholar Project of Shandong Province of China
- Chinese Postdoctoral Science Foundation [2016M602166]
- Research Award Funds for Outstanding Young Scientists of Shandong Province [BS20145F005]
- Special Funds for Postdoctoral Innovative Projects of Shandong Province [201403009]
- Fund for Postdoctoral Applied Research Projects of Qingdao [2016116]
This paper focuses on the stability problem for delayed complex-valued recurrent neural networks. Whether the complex-valued activation functions are explicitly expressed by separating real and imaginary parts or not, they are always assumed to satisfy the globally Lipschitz condition in the complex domain. For two cases of the activation functions, based on the homeomorphism theory and Lyapunov function approach new delay-dependent sufficient conditions to guarantee the existence, uniqueness, and globally asymptotical stability of the equilibrium point of system are obtained, respectively. For each case, several numerical examples are given to show the effectiveness and the advantages of the obtained results. (C) 2017 Elsevier B.V. All rights reserved.
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