Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 22, Issue 12, Pages 2138-2143Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2011.2169425
Keywords
Asymptotic stability; delay-slope-dependent; recurrent neural networks
Categories
Funding
- National Science Foundation of China [60904025, 60904026, 61174033]
- Key Laboratory of Education Ministry for Image Processing and Intelligent Control [200805]
- Australian Research Council
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By using the fact that the neuron activation functions are sector bounded and nondecreasing, this brief presents a new method, named the delay-slope-dependent method, for stability analysis of a class of recurrent neural networks with time-varying delays. This method includes more information on the slope of neuron activation functions and fewer matrix variables in the constructed Lyapunov-Krasovskii functional. Then some improved delay-dependent stability criteria with less computational burden and conservatism are obtained. Numerical examples are given to illustrate the effectiveness and the benefits of the proposed method.
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