Lag synchronization of switched neural networks via neural activation function and applications in image encryption
journal contributionposted on 09.04.2015 by Shiping Wen, Zhigang Zeng, Tingwen Huang, Qinggang Meng, Wei Yao
Any type of content formally published in an academic journal, usually following a peer-review process.
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.
This work was supported by the Qatar National Research Fund (Grant no. 4-1162-1-181);the Program for the Changjiang Scholars and Innovative Research Team in the University of China (Grant no. IRT1245); the National Natural Science Foundation of China (Grant numbers: 61125303, 61203286, and 61403152); and the National Basic Research Program (973 Program) of China (Grant no. 2011CB710606).
- Computer Science