Cargando…
Nonlinear system identification: from classical approaches to neural networks, fuzzy models, and Gaussian processes
This book provides engineers and scientists in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. It equips them to apply the models and methods discussed to real problems with confidence, while also making them aware of potential dif...
| Autor principal: | |
|---|---|
| Lenguaje: | eng |
| Publicado: |
Springer
2020
|
| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1007/978-3-030-47439-3 http://cds.cern.ch/record/2740517 |