Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 19, Issue 3, Pages 532-535Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2007.912593
Keywords
global asymptotic stability; Hopfield neural network (HNN); linear matrix inequality (LMI); Lyapunov functional
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In this brief, the problem of global asymptotic stability for delayed Hopfield neural networks (HNNs) is investigated. A new criterion of asymptotic stability is derived by introducing a new kind of Lyapunov-Krasovskii functional and is formulated in terms of a linear matrix inequality (LMI), which can be readily solved via standard software. This new criterion based on a delay fractioning approach proves to be much less conservative and the conservatism could be notably reduced by thinning the delay fractioning. An example is provided to show the effectiveness and the advantage of the proposed result.
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