Name
Title | ||
|---|---|---|
Sine neural network (SNN) with double-stage weights and structure determination (DS-WASD). |
Abstract | ||
|---|---|---|
To solve complex problems such as multi-input function approximation by using neural networks and to overcome the inherent defects of traditional back-propagation neural networks, a single hidden-layer feed-forward sine-activated neural network, sine neural network (SNN), is proposed and investigated in this paper. Then, a double-stage weights and structure determination (DS-WASD) method, which is based on the weights direct determination method and the approximation theory of using linearly independent functions, is developed to train the proposed SNN. Such a DS-WASD method can efficiently and automatically obtain the relatively optimal SNN structure. Numerical results illustrate the validity and efficacy of the SNN model and the DS-WASD method. That is, the proposed SNN model equipped with the DS-WASD method has great performance of approximation on multi-input function data. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s00500-014-1491-6 | soft computing |
Keywords | Field | DocType |
Sine neural network (SNN), Double-stage weights and structure determination (DS-WASD), Function approximation, Linear independence | Linear independence,Function approximation,Computer science,Sine,Algorithm,Approximation theory,Artificial intelligence,Artificial neural network,Machine learning,Complex problems | Journal |
Volume | Issue | ISSN |
20 | 1 | 1433-7479 |
Citations | PageRank | References |
1 | 0.35 | 12 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yunong Zhang | 1 | 2344 | 162.43 |
| Lu Qu | 2 | 1 | 0.35 |
| Jinrong Liu | 3 | 1 | 0.35 |
| Dongsheng Guo | 4 | 22 | 2.12 |
| Mingming Li | 5 | 1 | 0.35 |