Determining Solutions of Fuzzy Cellular Neural Networks with Fluctuating Delays

This pap er deals with the problem of nonp erio dic arrange ments for fuzzy cell neuralsystems with fluctuating delays. By utiliz ing c ompre ssion mapping and Krasnoselski’ssettled p oint hyp othesis and developing some appropriate Lyapunov functionals, ade quateconditions are s et up for the presence and worldwide exp onential solidness of solutions ofFCNNs with fluctuating delays. In addition, illustrative examples are set up to exhibit amo del

Exponential Stability of Cohen-Grossberg Neural Networks with Impulse Time Window

This paper concerns the problem of exponential stability for a class of Cohen-Grossberg neural networks with impulse time window and time-varying delays. In our letter, the impulsive effects we considered can stochastically occur at a definitive time window and the impulsive controllers we considered can be nonlinear and even rely on the states of all the neurons. Hence, the impulses here can be more applicable and more general. By utilizing Lyapunov functional theory, inequality technique, and the analysis method, we obtain some novel and effective exponential stability criteria for the Cohen-Grossberg neural networks. These results generalize a few previous known results and numerical simulations are given to show the effectiveness of the derived results