Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption
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, s...
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Published in | IEEE transaction on neural networks and learning systems Vol. 26; no. 7; pp. 1493 - 1502 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.07.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | 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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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 2162-237X 2162-2388 2162-2388 |
DOI: | 10.1109/TNNLS.2014.2387355 |