期刊
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
卷 43, 期 9, 页码 6093-6102出版社
WILEY
DOI: 10.1002/mma.6350
关键词
antiperiodic; proportional delay; recurrent neural network; stability
资金
- National Natural Science Foundation of China [11971076, 51839002]
In general, a proportional function is obviously not antiperiodic, yet a very interesting fact in this paper shows that it is possible there is an antiperiodic solution for some proportional delayed dynamical systems. We deal with the issue of antiperiodic solutions for RNNs (recurrent neural networks) incorporating multiproportional delays. Employing Lyapunov method, inequality techniques and concise mathematical analysis proof, sufficient criteria on the existence of antiperiodic solutions including its uniqueness and exponential stability are built up. The obtained results provide us some lights for designing a stable RNNs and complement some earlier publications. In addition, simulations show that the theoretical antiperiodic dynamics are in excellent agreement with the numerically observed behavior.
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