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

Aidi Liu; Hui Zhao; Qingjie Wang; Sijie Niu; Xizhan Gao; Zhen Su; Lixiang Li

doi:10.3389/fnbot.2022.1000426

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

Front Neurorobot. 2022 Oct 17:16:1000426. doi: 10.3389/fnbot.2022.1000426. eCollection 2022.

Authors

Aidi Liu¹, Hui Zhao¹, Qingjie Wang¹, Sijie Niu¹, Xizhan Gao¹, Zhen Su², Lixiang Li³

Affiliations

¹ Shandong Provincial Key Laboratory of Network Based Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, China.
² College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China.
³ State Key Laboratory of Networking and Switching Technology, Information Security Center, Beijing University of Posts and Telecommunications, Beijing, China.

Abstract

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.

Keywords: bidirectional associative memory; complex-valued neural networks; fixed-time synchronization; image encryption and decryption; predefined-time synchronization.