期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 32, 期 1, 页码 151-165出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2020.2977614
关键词
Synchronization; Encryption; Artificial neural networks; Memristors; Chaotic communication; Mathematical model; Complex-valued neural networks (NNs); exponential synchronization; image encryption; memristor; uncertainties
类别
资金
- National Industrial Internet Security Public Service Platform
- National Key Research and Development Program of China [2018YFB0803505]
- National Natural Science Foundation of China [81961138010, U1803263, 11931015, U1736117, U1836106]
- University of Science and Technology Beijing (USTB) [FRF-BD-19-012A]
- Beijing Natural Science Foundation [19L2029]
- Technological Innovation Foundation of Shunde Graduate School, USTB [BK19BF006]
- Key Area Research and Development Program of Guangdong Province [2019B010137004]
- Key Area Research and Development Program of Shanxi Province [2019ZDLGY17-07]
- Fundamental Research Funds for the Central Universities [3102019PJ006]
This article addresses the exponential synchronization issue of memristor-based complex-valued neural networks with time-varying uncertainties by feedback control. The proposed algorithm not only ensures the stability of the system, but also converts the sensitivity measure of encryption and decryption into synchronization error, suitable for image protection. Simulation examples are provided to verify the efficacy of the proposed synchronization criterion and its practical application on image protection.
This article solves the exponential synchronization issue of memristor-based complex-valued neural networks (MCVNNs) with time-varying uncertainties via feedback control. Compared with the traditional control methods, a more practical and general control scheme with the available uncertain information of the parameters is newly developed for MCVNNs. Our approach considers the proposed neural networks as two dynamic real-valued systems. Then, the less conservative exponential synchronization criteria are proposed by incorporating the framework of the Lyapunov method and inequality techniques. Under the proposed algorithm, not only can the stability of MCVNNs be guaranteed but also the behavior of such a system is appropriate for image protection. Meanwhile, the sensitive measure of the encryption and decryption can be converted into synchronization error. When monitoring the secure mechanism as a whole, the influence of error feasible domain on image decryption is analyzed. Simulation examples are provided to verify the efficacy of the proposed synchronization criterion and the results of practical application on image protection.
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