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Proceedings of ELM-2017 - Proceedings in Adaptation, Learning and Optimization Softcover Reprint of the Original 1st 2019 edition
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Proceedings of ELM-2017 - Proceedings in Adaptation, Learning and Optimization
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.
| Mediji | Grāmatas Paperback Book (Grāmata ar mīksto vāku un līmēto muguru) |
| Izlaists | 2019. gada 10. decembris |
| ISBN13 | 9783030131821 |
| Izdevēji | Springer Nature Switzerland AG |
| Lapas | 340 |
| Izmēri | 150 × 220 × 10 mm · 534 g |
| Valoda | Vācu |
| Redaktors | Cao, Jiuwen |
| Redaktors | Lendasse, Amaury |
| Redaktors | Miche, Yoan |
| Redaktors | Vong, Chi Man |
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