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Exponential Lag Synchronization of Memristive Neural Networks with Reaction Diffusion Terms via Neural Activation Function Control and Fuzzy Model
Author(s) -
Liu Yicheng,
Liao Xiaofeng,
Li Chuandong
Publication year - 2020
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1862
Subject(s) - control theory (sociology) , artificial neural network , memristor , synchronization (alternating current) , activation function , reaction–diffusion system , fuzzy logic , controller (irrigation) , exponential function , computer science , mathematics , topology (electrical circuits) , control (management) , artificial intelligence , engineering , electronic engineering , combinatorics , biology , mathematical analysis , agronomy
This paper is concerned with the problem of exponential lag synchronization of memristive neural networks with reaction diffusion terms via neural activation function control and fuzzy model. An memristor‐based circuit which exhibits the feature of pinched hysteresis is introduced and further, the memristive neural networks with reaction diffusion terms and such system containing fuzzy model are described at length, respectively. By utilizing the Lyapunov functional method and the neural activation function controller depending on the output of the system in the case of packed circuits, some concise conditions are acquired to guarantee the slave systems exponential lag synchronized with the master systems. Finally, several simulated examples are also presented to demonstrate the correctness of the theoretical results.