Abstract
This paper focuses on the dynamical characteristics of complex-valued memristor-based BAM neural network (CVMBAMNN) with leakage time-varying delay. With two different controllers, we have obtained fixedtime and finite-time synchronization criteria respectively in complex domain for our special model, which few work has studied before. Since fixed-time synchronous system can improve communication security, we designed a scheme for RGB image encryption and decryption. In order to satisfy the requirement of much lower error in image secure communication, our approach can get the error of fixed-time synchronization to about 1×10−13. Due to our highly consistent system, we do get good encryption and decryption effect with encryption and decryption scheme. Finally, numerical simulations are included to demonstrate the correctness of our theoretical results.
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Recommended by Associate Editor Ohmin Kwon under the direction of Editor Euntai Kim. This work was supported in part by the National Key Research and Development Program of China under Grant 2016YFB0800205, and the National Key Research and Development Program of China under Grant No. 2018YFB0803505, and the National Natural Science Foundation of China under Grants U1836106, the State Scholarship Fund of China Scholarship Council (CSC), the Fundamental Research Funds for the Central Universities under Grant 06500025, the National Nature Science Foundation of China under Grant U1836106, and the University of Science and Technology Beijing-National Taipei University of Technology Joint Research Program under Grant TW201705.
Yongzhen Guo received his master degree of Control Theory and Control Engineering from Tianjin University, Tianjin, China. He is studying for a Ph.D. at Beijing University of Technology. He is also the General Manager of Industrial Control System Evaluation and Certification Department of China Software Testing Center. He received National Science and Technology Major Projects, and National Key Research and Development Programs. His research area is security and cryptography, safety and reliability, and system evaluation and certification. As a member of SAC/TC124/SC10, SAC/TC196, ISO/TC 199/WG8, IEC/TC65/SC65C/WG18, he is participating in a number of international standards and national standards setting and revising.
Yang Luo is currently pursuing a bachelor’s degree in intelligent science and technology from University of Science and Technology Beijing, Beijing, China. His current research interests include memristive neural networks, system control and chaotic image encryption and decryption.
Weiping Wang received her Ph.D. degree in telecommunications physics electronics from Beijing University of Posts and Telecommunications, Beijing, China, in 2015. She is currently an Associate Professor with the Department of Computer and Communication Engineering, University of Science and Technology Beijing. She received the the National Key Research and Development Program of China, the State Scholarship Fund of China Scholarship Council, National Natural Science Foundation of China, the Postdoctoral fund, and the basic scientific research project. Her current research interests include brain-like computing, memrisitive neural network, associative memory awareness simulation, complex network, network security and image encryption.
Xiong Luo received his Ph.D. degree in computer applied technology from Central South University, Changsha, China, in 2004. He is currently a Professor with the School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China. His current research interests include neural networks, machine learning, and computational intelligence. He has published extensively in his areas of interest in several journals, such as IEEE ACCESS, Future Generation Computer Systems, and Personal and Ubiquitous Computing.
Chao Ge received his Ph.D. degree in electrical engineering from Yanshan University, Qinhuangdao, China, in 2015. Now he is an Associate Professor in North China University of Science and Technology, China. His research interests are in time-delay systems, neural networks, fuzzy systems and networked control systems.
Jürgen Kurths studied mathematics at the University of Rostock and received his Ph.D. degree in 1983 from the GDR Academy of Sciences. He was a full professor at the University of Potsdam from 1994 to 2008 and has been a professor of nonlinear dynamics at the Humboldt University, Berlin, and the chair of the research domain Transdisciplinary Concepts of the Potsdam Institute for Climate Impact Research since 2008 and a sixth-century chair of Aberdeen University, United Kingdom, since 2009. He is a fellow of the American Physical Society. He received the Alexander von Humboldt Research Award from CSIR, India, in 2005 and an honorary doctorate in 2008 from the Lobachevsky University Nizhny Novgorod and one in 2012 from the State University Saratov. He became a member of the Academia Europaea in 2010 and of the Macedonian Academy of Sciences and Arts in 2012. His primary research interests include synchronization, complex networks, and time series analysis and their applications. He has published more than 500 papers that are cited more than 18,000 times (H-factor: 57). He is an editor of journals such as PLoS ONE, the Philosophical Transaction of the Royal Society A, the Journal of Nonlinear Science, and Chaos.
Manman Yuan received her M.S. degree in computer science and technology from Inner Mongolia University of Science and Technology, Baotou, China, in 2015, where she is currently pursuing a Ph.D. degree from University of Science and Technology Beijing, Beijing, China. Her current research interests include memristive neural networks and brain computing.
Yang Gao is an assistant research fellow with the China Information Technology Security Evaluation Center. She received her M.S. degree in applied mathematics and her Ph.D. degree in information security from Beijing University of Posts and Telecommunications, China. Her current research interests include information security, complex networks, cyber-physical system, ICS security.
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Guo, Y., Luo, Y., Wang, W. et al. Fixed-time Synchronization of Complex-valued Memristive BAM Neural Network and Applications in Image Encryption and Decryption. Int. J. Control Autom. Syst. 18, 462–476 (2020). https://doi.org/10.1007/s12555-018-0676-7
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DOI: https://doi.org/10.1007/s12555-018-0676-7