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Fixed‐time synchronization for complex‐valued BAM neural networks with time delays
Author(s) -
Zhang Ziye,
Guo Runan,
Liu Xiaoping,
Zhong Maiying,
Lin Chong,
Chen Bing
Publication year - 2021
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.2185
Subject(s) - settling time , synchronization (alternating current) , control theory (sociology) , artificial neural network , nonlinear system , computer science , controller (irrigation) , stability (learning theory) , bidirectional associative memory , content addressable memory , mathematics , control (management) , control engineering , engineering , artificial intelligence , computer network , agronomy , channel (broadcasting) , physics , quantum mechanics , machine learning , biology , step response
Abstract In this paper, the fixed‐time synchronization for complex‐valued bidirectional associative memory (BAM) neural networks with time delays is studied. Based on the fixed‐time stability, the Lyapunov functional method and some inequality techniques, a new criterion is presented to guarantee that the addressed systems achieve synchronization in fixed time and a more accurate estimation independent of the initial conditions is given for the settling time. Meanwhile, a new nonlinear delayed controller different from the existing ones is designed. In the end, two numerical examples are provided to illustrate the effectiveness of the obtained result.