Proceedings of ELM-2017
BOK (Häftad)
- Springer Nature Switzerland AG
- 2019-12-10
- Engelska
ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series,etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments.
| Serie: | Proceedings in Adaptation, Learning and Optimization |
| Redaktör: | Cao, Jiuwen, Vong, Chi Man, Miche, Yoan, Lendasse, Amaury |
| Upplaga: | Softcover Reprint of the Original 1st 2019 ed. |
| Höjd: | 235 mm |
| Bredd: | 155 mm |
| Omfång: | 340 s. |
| Övrig information: | Switzerland, Springer Nature Switzerland AG |
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