Existence and attractivity of periodic solutions to Cohen-Grossberg neural network with distributed delays.
Existence and exponential stability for anti-periodic solutions for shunting inhibitory cellular neural networks with continuously distributed delays.
Existence and exponential stability of a periodic solution for fuzzy cellular neural networks with time-varying delays
Fuzzy cellular neural networks with time-varying delays are considered. Some sufficient conditions for the existence and exponential stability of periodic solutions are obtained by using the continuation theorem based on the coincidence degree and the differential inequality technique. The sufficient conditions are easy to use in pattern recognition and automatic control. Finally, an example is given to show the feasibility and effectiveness of our methods.
Existence and exponential stability of periodic solution for a class of generalized neural networks with arbitrary delays.
Existence and exponential stability of periodic solution of high-order Hopfield neural network with delays on time scales.
Existence and global exponential stability of almost periodic solutions for SICNNs with nonlinear behaved functions and mixed delays.
Existence and global exponential stability of equilibrium solution to reaction-diffusion recurrent neural networks on time scales.
Existence and global exponential stability of periodic solutions for general neural networks with time-varying delays.
Existence and global stability of periodic solution for delayed discrete high-order Hopfield-type neural networks.
Existence and stability of almost periodic solutions for shunting inhibitory cellular neural networks with continuously distributed delays.
Existence and stability of antiperiodic solution for a class of generalized neural networks with impulses and arbitrary delays on time scales.
Existence and stability of periodic solutions for a class of generalized nonautonomous neural networks with distributed delays.
Existence of almost periodic solutions for Hopfield neural networks with continuously distributed delays and impulses.
Existence, uniqueness and global asymptotic stability for a class of complex-valued neutral-type neural networks with time delays
This paper explores the problem of delay-independent and delay-dependent stability for a class of complex-valued neutral-type neural networks with time delays. Aiming at the neutral-type neural networks, an appropriate function is constructed to derive the existence of equilibrium point. On the basis of homeomorphism theory, Lyapunov functional method and linear matrix inequality techniques, several LMI-based sufficient conditions on the existence, uniqueness and global asymptotic stability of equilibrium...
Exponential convergence for BAM neural networks with distributed delays.
Exponential convergence of shunting inhibitory cellular neural networks with continuously distributed delays
We study delay shunting inhibitory cellular neural networks without almost periodic coefficients. Some sufficient conditions are established to ensure that all solutions of the networks converge exponentially to an almost periodic function. This complements previously known results.
Exponential convergence of solutions of SICNNs with mixed delays.
Finite-time adaptive outer synchronization between two complex dynamical networks with nonidentical topological structures
In this paper, we investigate the finite-time adaptive outer synchronization between two complex dynamical networks with nonidentical topological structures. We propose new adaptive controllers, with which we can synchronize two complex dynamical networks within finite time. Sufficient conditions for the finite-time adaptive outer synchronization are derived based on the finite-time stability theory. Finally, numerical examples are examined to demonstrate the effectiveness and feasibility of the...
General results on the existence and global exponential stability of periodic solutions for generalized shunting inhibitory cellular neural networks with delays.
Global dissipativity on uncertain discrete-time neural networks with time-varying delays.