180 research outputs found
Stability Results for Uncertain Stochastic High-Order Hopfield Neural Networks with Time Varying Delays
On the stability of impulsive functional differential equations with infinite delays
In this paper, the stability problem of impulsive functional differential equations with infinite delays is considered. By using Lyapunov functions and the Razumikhin technique, some new theorems on the uniform stability and uniform asymptotic stability are obtained. The obtained results are milder and more general than several recent works. Two examples are given to demonstrate the advantages of the results
SATURATED AND ASYMMETRIC SATURATED IMPULSIVE CONTROL SYNCHRONIZATION OF COUPLED DELAYED INERTIAL NEURAL NETWORKS WITH TIME-VARYING DELAYS
This paper considers control systems with impulses that are saturated and asymmetrically saturated which are used to examine the synchronization of inertial neural networks (INNs) with time-varying delay and coupling delays. Under the theoretical discussions, mixed delays, such as transmission delay and coupling delay are presented for inertial neural networks. The addressed INNs are transformed into first order differential equations utilizing variable transformation on INNs and then certain adequate conditions are derived for the exponential synchronization of the addressed model by substituting saturation nonlinearity with a dead-zone function. In addition, an asymmetric saturated impulsive control approach is given to realize the exponential synchronization of addressed INNs in the leader-following synchronization pattern. Finally, simulation results are used to validate the theoretical research findings
Delay-dependent exponential stability results for uncertain stochastic Hopfield neural networks with interval time-varying delays
Exponential stability for fuzzy BAM cellular neural networks with distributed leakage delays and impulses
Anti-synchronization control for delayed memristor-based distributed parameter NNs with mixed boundary conditions
On extended dissipativity analysis for neural networks with time-varying delay and general activation functions
- …