Reachable Set Estimation for a Class of Memristor-Based Neural Networks With Time-Varying Delays
作者： Jiemei Zhao
DOI: 10.1109/ACCESS.2017.2777008
关键词:
摘要: This paper investigates the reachable set estimation problem for a class of memristor-based neural networks with time-varying delays and bounded disturbances. By constructing Lyapunov–Krasovskii functional, sufficient condition solvability addressed is established based on linear matrix inequality. ensuring existence an ellipsoid that contains all states under initial conditions. A stability criterion also given. Two numerical examples are provided to show effectiveness proposed methods.
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