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Projective Synchronization of Delayed Uncertain Coupled Memristive Neural Networks and Their Application.
Han, Zhen; Chen, Naipeng; Wei, Xiaofeng; Yuan, Manman; Li, Huijia.
Afiliação
  • Han Z; School of Cybersecurity, Northwestern Polytechnical University, Xi'an 710072, China.
  • Chen N; International School, Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Wei X; The 20th Research Institute of China Electronics Technology Group Corporation, Xi'an 710068, China.
  • Yuan M; School of Computer Science, Inner Mongolia University, Hohhot 010021, China.
  • Li H; School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Entropy (Basel) ; 25(8)2023 Aug 21.
Article em En | MEDLINE | ID: mdl-37628273
ABSTRACT
In this article, the authors analyzed the nonlinear effects of projective synchronization between coupled memristive neural networks (MNNs) and their applications. Since the complete signal transmission is difficult under parameter mismatch and different projective factors, the delays, which are time-varying, and uncertainties have been taken to realize the projective synchronization of MNNs with multi-links under the nonlinear control method. Through the extended comparison principle and a new approach to dealing with the mismatched parameters, sufficient criteria have been determined under different types of projective factors and the framework of the Lyapunov-Krasovskii functional (LKF) for projective convergence of the coupled MNNs. Instead of the classical treatment for secure communication, the concept of error of synchronization between the drive and response systems has been applied to solve the signal encryption/decryption problem. Finally, the simulations in numerical form have been demonstrated graphically to confirm the adaptability of the theoretical results.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Entropy (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China