Global Exponential Stability for Uncertain Delayed Neural Networks of Neutral Type With Mixed Time Delays
Chang‐Hua Lien, Ker‐Wei Yu, Yen‐Feng Lin, Yeong-Jay Chung, Long‐Yeu Chung · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · 2008
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.