Exponential Stability of Cohen-Grossberg Neural Networks with Impulse Time Window
作者： Mei Liu , Haijun Jiang , Cheng Hu
DOI: 10.1155/2016/2762960
关键词: Lyapunov functional 、 Mathematics 、 Analysis method 、 Control theory 、 Time windows 、 Impulse (physics) 、 Artificial neural network 、 Exponential stability 、 Nonlinear system
摘要: This paper concerns the problem of exponential stability for a class Cohen-Grossberg neural networks with impulse time window and time-varying delays. In our letter, impulsive effects we considered can stochastically occur at definitive controllers be nonlinear even rely on states all neurons. Hence, impulses here more applicable general. By utilizing Lyapunov functional theory, inequality technique, analysis method, obtain some novel effective criteria networks. These results generalize few previous known numerical simulations are given to show effectiveness derived results.
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