Name
Abstract | ||
|---|---|---|
In this paper, we investigate stability of a class of analytic neural networks with the synaptic feedback via event-triggered rules. This model is general and include Hopfield neural network as a special case. These event-trigger rules can efficiently reduces loads of computation and information transmission at synapses of the neurons. The synaptic feedback of each neuron keeps a constant value ba... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TNNLS.2015.2488903 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Neurons,Trajectory,Biological neural networks,Lyapunov methods,Stability criteria,Numerical stability | Computer science,Information transmission,Event triggered,Artificial intelligence,Artificial neural network,Machine learning,Numerical stability,Trajectory,Computation,Special case | Journal |
Volume | Issue | ISSN |
27 | 2 | 2162-237X |
Citations | PageRank | References |
5 | 0.42 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ren Zheng | 1 | 26 | 2.22 |
| Xinlei Yi | 2 | 18 | 1.44 |
| Wenlian Lu | 3 | 370 | 25.19 |
| Tianping Chen | 4 | 3095 | 250.77 |