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Deep Learning in Multi-step Prediction of Chaotic Dynamics: From Deterministic Models to Real-World Systems - SpringerBriefs in Applied Sciences and Technology Matteo Sangiorgio 1st ed. 2021 edition
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Deep Learning in Multi-step Prediction of Chaotic Dynamics: From Deterministic Models to Real-World Systems - SpringerBriefs in Applied Sciences and Technology
Matteo Sangiorgio
The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series.
104 pages, 50 Tables, color; 25 Illustrations, color; 21 Illustrations, black and white; XII, 104 p.
| Mediji | Grāmatas Paperback Book (Grāmata ar mīksto vāku un līmēto muguru) |
| Izlaists | 2022. gada 15. februāris |
| ISBN13 | 9783030944810 |
| Izdevēji | Springer Nature Switzerland AG |
| Lapas | 104 |
| Izmēri | 150 × 220 × 10 mm · 191 g |
| Valoda | Vācu |