Fixed/Predefined-time synchronization of memristor-based complex-valued BAM neural networks for image protection.

Autor:	Liu A; Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China., Zhao H; Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China., Wang Q; Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China., Niu S; Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China., Gao X; Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China., Su Z; College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China., Li L; State Key Laboratory of Networking and Switching Technology, Information Security Center, Beijing University of Posts and Telecommunications, Beijing, China.
Jazyk:	angličtina
Zdroj:	Frontiers in neurorobotics [Front Neurorobot] 2022 Oct 17; Vol. 16, pp. 1000426. Date of Electronic Publication: 2022 Oct 17 (Print Publication: 2022).
DOI:	10.3389/fnbot.2022.1000426
Abstrakt:	This paper investigates the fixed-time synchronization and the predefined-time synchronization of memristive complex-valued bidirectional associative memory neural networks (MCVBAMNNs) with leakage time-varying delay. First, the proposed neural networks are regarded as two dynamic real-valued systems. By designing a suitable feedback controller, combined with the Lyapunov method and inequality technology, a more accurate upper bound of stability time estimation is given. Then, a predefined-time stability theorem is proposed, which can easily establish a direct relationship between tuning gain and system stability time. Any predefined time can be set as controller parameters to ensure that the synchronization error converges within the predefined time. Finally, the developed chaotic MCVBAMNNs and predefined-time synchronization technology are applied to image encryption and decryption. The correctness of the theory and the security of the cryptographic system are verified by numerical simulation. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Liu, Zhao, Wang, Niu, Gao, Su and Li.)
Databáze:	MEDLINE
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