Name
Title | ||
|---|---|---|
Global exponential stability of delayed reaction-diffusion neural networks with time-varying coefficients |
Abstract | ||
|---|---|---|
In the current paper, a class of general neural networks with time-varying coefficients, reaction-diffusion terms, and general time delays is studied. Several sufficient conditions guaranteeing its global exponential stability and the existence of periodic solutions are obtained through analytic methods such as Lyapunov functional and Poincare mapping. The obtained results assume no boundedness, monotonicity or differentiability of activation functions and can be applied within a broader range of neural networks. Among the presented conditions, some are independent of time delay and expressed in terms of system parameters, so easy to verify and of leading significance in applications. For illustration, an example is given. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.eswa.2009.02.018 | Expert Syst. Appl. |
Keywords | Field | DocType |
poincaré mapping,lyapunov functional,neural network,poincare mapping,neural networks,time-varying coefficient,exponential stability,general neural network,delayed reaction-diffusion neural network,broader range,current paper,general time delay,global exponential stability,activation function,analytic method,time delay,reaction–diffusion,reaction diffusion,generation time,lyapunov function | Poincare mapping,Monotonic function,Mathematical analysis,Differentiable function,Exponential stability,Artificial neural network,Periodic graph (geometry),Lyapunov functional,Reaction–diffusion system,Mathematics | Journal |
Volume | Issue | ISSN |
36 | 6 | Expert Systems With Applications |
Citations | PageRank | References |
8 | 0.69 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ranchao Wu | 1 | 189 | 10.45 |
| Weiwei Zhang | 2 | 11 | 1.05 |