期刊
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷 26, 期 7, 页码 1493-1502出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2014.2387355
关键词
Exponential stability; lag synchronization; switched neural networks
类别
资金
- Qatar National Research Fund, a member of the Qatar Foundation through the National Priorities Research Programme [4-1162-1-181]
- Program for the Changjiang Scholars and Innovative Research Team in the University of China [IRT1245]
- National Natural Science Foundation of China [61125303, 61203286, 61403152]
- National Basic Research Program (973 Program) of China [2011CB710606]
This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the output of the system in the case of packed circuits, since it is hard to measure the inner state of the circuits. Thus, it is critical to design the controller based on the neuron activation function. Comparing the results, in this paper, with the existing ones shows that we improve and generalize the results derived in the previous literature. Several examples are also given to illustrate the effectiveness and potential applications in image encryption.
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