Recurrent neural networks for prediction: learning algorithms, architectures and stability
Not available
Not available
0471495174
Wiley series in adaptive and learning systems for signal processing, communications, and control
Not available
Appendix: p. 223 - 266
New technologies in engineering, physics and biomedicine are demanding increasingly complex methods of digital signal processing. By presenting the latest research work the authors demonstrate how real-time recurrent neural networks (RNNs) can be implemented to expand the range of traditional signal processing techniques and to help combat the problem of prediction. Within this text neural networks are considered as massively interconnected nonlinear adaptive filters.
xxi, 285 p.
25 cm.
ill.
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| Access no. | Call number | Location | Status |
|---|---|---|---|
| 01970/08 | 006.32 Man R | Library - 7th Floor | Available |
