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Finite‐time synchronization and adaptive synchronization of memristive recurrent neural networks with delays
Author(s) -
Li Xiaofan,
Fang Jianan,
Li Huiyuan
Publication year - 2018
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2917
Subject(s) - synchronization (alternating current) , settling time , control theory (sociology) , computer science , adaptive control , artificial neural network , lyapunov stability , control (management) , control engineering , engineering , artificial intelligence , step response , channel (broadcasting) , computer network
Summary This paper solves the finite‐time synchronization and adaptive synchronization problems of drive‐response memristive recurrent neural networks with delays under two control methods. First, the state‐feedback control rule containing delays and the adaptive control rule are designed for realizing synchronization of drive‐response memristive recurrent neural networks in finite time. Then, on the basis of the Lyapunov stability theory, many algebraic sufficient conditions are obtained to guarantee finite‐time synchronization and adaptive synchronization of drive‐response memristive recurrent neural networks via two control methods, which are easily verified. In addition, the estimation of the upper bounds of the settling time of finite‐time synchronization is obtained. Lastly, to illustrate the effectiveness of the obtained theoretical results, two examples are given.