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Improved global robust asymptotic stability criteria for delayed cellular neural networks

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4 Author(s)
Shengyuan Xu ; Dept. of Autom., Nanjing Univ. of Sci. & Technol., China ; Lam, J. ; Ho, D.W.C. ; Yun Zou

This paper considers the problem of global robust stability analysis of delayed cellular neural networks (DCNNs) with norm-bounded parameter uncertainties. In terms of a linear matrix inequality, a new sufficient condition ensuring a nominal DCNN to have a unique equilibrium point which is globally asymptotically stable is proposed. This condition is shown to be a generalization and improvement over some previous criteria. Based on the stability result, a robust stability condition is developed, which contains an existing robust stability result as a special case. An example is provided to demonstrate the reduced conservativeness of the proposed results.

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Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:35 ,  Issue: 6 )