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• W2034779834 abstract "In this paper, the exponential stability problem is investigated for a class of Cohen–Grossberg-type bidirectional associative memory neural networks with time-varying delays. By using the analysis method, inequality technique and the properties of an M-matrix, several novel sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are derived. Moreover, the exponential convergence rate is estimated. The obtained results are less restrictive than those given in the earlier literature, and the boundedness and differentiability of the activation functions and differentiability of the time-varying delays are removed. Two examples with their simulations are given to show the effectiveness of the obtained results." @default.
• W2034779834 created "2016-06-24" @default.
• W2034779834 creator A5017808266 @default.
• W2034779834 creator A5047077749 @default.
• W2034779834 date "2006-06-09" @default.
• W2034779834 modified "2023-10-13" @default.
• W2034779834 title "Stability in Cohen–Grossberg-type bidirectional associative memory neural networks with time-varying delays" @default.
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• W2034779834 doi "https://doi.org/10.1088/0951-7715/19/7/008" @default.
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