Name
Abstract | ||
|---|---|---|
The paper deals with a discrete-time recurrent neural network designed with dynamic neural models. Dynamics is reproduced within each single neuron, hence the considered network is a locally recurrent globally feed-forward. In the paper, conditions for global stability of the considered neural network are derived using the pole placement and Lyapunov second method. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11550907_31 | ICANN (2) |
Keywords | Field | DocType |
single neuron,neural network,paper deal,global stability,pole placement,considered network,global stability condition,dynamic neural model,discrete-time recurrent neural network,recurrent neural network,discrete time,feed forward | Lyapunov function,Recurrent neural nets,Full state feedback,Computer science,Control theory,Recurrent neural network,Stability conditions,Discrete time and continuous time,Artificial neural network,Feed forward | Conference |
Volume | ISSN | ISBN |
3697 | 0302-9743 | 3-540-28755-8 |
Citations | PageRank | References |
1 | 0.41 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Krzysztof Patan | 1 | 151 | 18.13 |
| Józef Korbicz | 2 | 127 | 16.23 |
| Przemysław Pretki | 3 | 21 | 3.26 |