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...

Full description

Saved in:
Bibliographic Details
Published inIEEE transaction on neural networks and learning systems Vol. 26; no. 7; pp. 1493 - 1502
Main Authors Wen, Shiping, Zeng, Zhigang, Huang, Tingwen, Meng, Qinggang, Yao, Wei
Format Journal Article
LanguageEnglish
Published United States IEEE 01.07.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text

Cover

Loading…
More Information
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.
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