Name
Abstract | ||
|---|---|---|
Neural networks (NNs) in the stochastic environment were widely modeled as stochastic differential equations, which were driven by white noise, such as Brown or Wiener process in the existing papers. However, they are not necessarily the best models to describe dynamic characters of NNs disturbed by nonwhite noise in some specific situations. In this paper, general noise disturbance, which may be ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TNNLS.2016.2637567 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Artificial neural networks,Asymptotic stability,Stability criteria,Stochastic processes,Power system stability,Mathematical model | Wiener process,Lyapunov function,Random field,Control theory,Computer science,Stochastic process,White noise,Stochastic differential equation,Exponential stability,Artificial intelligence,Machine learning,Linear matrix inequality | Journal |
Volume | Issue | ISSN |
29 | 3 | 2162-237X |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qihe Shan | 1 | 182 | 14.01 |
| H Zhang | 2 | 7027 | 358.18 |
| Zhanshan Wang | 3 | 2194 | 106.95 |
| zhonghua zhang | 4 | 29 | 2.20 |