On Global Dissipativity of Nonautonomous Neural Networks With Multiple Proportional Delays

This brief addresses the problem of global dissipativity analysis of nonautonomous neural networks with multiple proportional delays. By using a novel constructive approach based on some comparison techniques for differential inequalities, new explicit delay-independent conditions are derived using...

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Bibliographic Details
Published in:IEEE transaction on neural networks and learning systems 2018-01, Vol.29 (1), p.225-231
Main Authors: Van Hien, Le, Son, Doan Thai, Trinh, Hieu
Format: Article
Language:English
Subjects:
Attracting sets
Delays
Dissipation
dissipativity
Inequalities
Learning systems
M-matrix
Mathematical model
Matrix theory
Neural networks
Neurons
proportional delays
Stability analysis
Trajectory
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Summary:This brief addresses the problem of global dissipativity analysis of nonautonomous neural networks with multiple proportional delays. By using a novel constructive approach based on some comparison techniques for differential inequalities, new explicit delay-independent conditions are derived using M-matrix theory to ensure the existence of generalized exponential attracting sets and the global dissipativity of the system. The method presented in this brief is also utilized to derive a generalized exponential estimate for a class of Halanay-type inequalities with proportional delays. Finally, three numerical examples are given to illustrate the effectiveness and improvement of the obtained results.
ISSN:2162-237X
2162-2388
DOI:10.1109/TNNLS.2016.2614998