Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 21, Issue 4, Pages 692-697Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2010.2042172
Keywords
Delay dependent; exponential stability; linear matrix inequality (LMI); neural networks; time-varying delays
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Funding
- National Creative Research Groups Science Foundation of China [60721062]
- National Natural Science Foundation of China [60736021]
- National High Technology Research and Development Program of China [2008AA042902]
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This brief investigates the problem of global exponential stability analysis for discrete recurrent neural networks with time-varying delays. In terms of linear matrix inequality (LMI) approach, a novel delay-dependent stability criterion is established for the considered recurrent neural networks via a new Lyapunov function. The obtained condition has less conservativeness and less number of variables than the existing ones. Numerical example is given to demonstrate the effectiveness of the proposed method.
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