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Proceedings of ELM 2017 1st ed. 2019 edition
Proceedings of ELM 2017
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.
340 pages, 130 Illustrations, black and white; VII, 340 p. 130 illus.
| 介质类型 | 图书 Book |
| 已发行 | 2018年10月17日 |
| ISBN13 | 9783030015190 |
| 出版商 | Springer Nature Switzerland AG |
| 页数 | 340 |
| 商品尺寸 | 150 × 220 × 20 mm · 688 g |
| 语言 | 德语 |
| 编辑 | Cao, Jiuwen |
| 编辑 | Lendasse, Amaury |
| 编辑 | Miche, Yoan |
| 编辑 | Vong, Chi Man |
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