Abstract
Recurrent neural networks are highly nonlinear dynamic systems, and therefore it is not an easy task to analyze their dynamic behavior. The primary goal of this paper is to apply Prony signal analysis and a modified root locus technique to recurrent neural networks. Prony method is compared with other linearization methods to analyze recurrent neural networks, and their performances are demonstrated using simulated examples.
| Original language | English (US) |
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| Title of host publication | IEEE International Conference on Neural Networks - Conference Proceedings |
| Publisher | IEEE Computer Society |
| Pages | 413-418 |
| Number of pages | 6 |
| Volume | 1 |
| State | Published - 1994 |
| Event | Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA Duration: Jun 27 1994 → Jun 29 1994 |
Other
| Other | Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) |
|---|---|
| City | Orlando, FL, USA |
| Period | 6/27/94 → 6/29/94 |
ASJC Scopus subject areas
- Software