1. Exponential Stability of Antiperiodic Solution for BAM Neural Networks with Time-Varying Delays
- Author
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Quanxin Zhu, Xiaofei Li, and Chuan Qin
- Subjects
Lyapunov function ,Artificial neural network ,Article Subject ,General Mathematics ,lcsh:Mathematics ,010102 general mathematics ,General Engineering ,02 engineering and technology ,lcsh:QA1-939 ,01 natural sciences ,symbols.namesake ,Exponential stability ,Control theory ,lcsh:TA1-2040 ,Negative feedback ,0202 electrical engineering, electronic engineering, information engineering ,symbols ,020201 artificial intelligence & image processing ,0101 mathematics ,lcsh:Engineering (General). Civil engineering (General) ,Mathematics ,Leakage (electronics) - Abstract
In this paper, a kind of BAM neural networks with leakage delays in the negative feedback terms and time-varying delays in activation functions was considered. By constructing a suitable Lyapunov function and using inequality techniques, some sufficient conditions to ensure the existence and exponential stability of antiperiodic solutions of these neural networks were derived. These conditions extend some results recently appearing in recent papers. Lastly, an example is given to show the feasibility of these conditions.
- Published
- 2018