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Global Exponential Stability for Uncertain Delayed Neural Networks of Neutral Type With Mixed Time Delays

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5 Author(s)
Chang-Hua Lien ; Dept. of Marine Eng., Nat. Kaohsiung Marine Univ., Kaohsiung ; Ker-Wei Yu ; Yen-Feng Lin ; Yeong-Jay Chung
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The global exponential stability for a class of uncertain delayed neural networks (DNNs) of neutral type with mixed delays is investigated in this paper. Delay-dependent and delay-independent stability criteria are proposed to guarantee the robust stability and uniqueness of equilibrium point of DNNs via linear matrix inequality and Razumikhin-like approaches. Two classes of perturbations on weighting matrices are considered in this paper. Some numerical examples are illustrated to show the effectiveness of our results.

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Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:38 ,  Issue: 3 )