Regularized System Identification : Learning Dynamic Models from Data
| 1. Verfasser: |
Pillonetto, Gianluigi
, [VerfasserIn]
Chen, Tianshi , [VerfasserIn] Chiuso, Alessandro , [VerfasserIn] De Nicolao, Giuseppe , [VerfasserIn] Ljung, Lennart , [VerfasserIn] |
|---|---|
| Umfang/Format: |
1 online resource (377 pages). |
| Schriftenreihe: |
Communications and Control Engineering
|
| Schlagworte: | |
| Online Zugang: |
DOAB: download the publication DOAB: description of the publication |
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| 100 | 1 | |a Pillonetto, Gianluigi |e author | |
| 264 | |b Springer Nature, |c 2022. | ||
| 700 | 1 | |a Chen, Tianshi |e author | |
| 700 | 1 | |a Chiuso, Alessandro |e author | |
| 700 | 1 | |a De Nicolao, Giuseppe |e author | |
| 700 | 1 | |a Ljung, Lennart |e author | |
| 245 | 1 | 0 | |a Regularized System Identification : |b Learning Dynamic Models from Data |
| 300 | |a 1 online resource (377 pages). | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Communications and Control Engineering | |
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 536 | |a National Natural Science Foundation of China | ||
| 540 | |a Creative Commons |f by/4.0/ |2 cc |4 http://creativecommons.org/licenses/by/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Machine learning |2 bicssc | |
| 650 | 7 | |a Automatic control engineering |2 bicssc | |
| 650 | 7 | |a Statistical physics |2 bicssc | |
| 650 | 7 | |a Bayesian inference |2 bicssc | |
| 650 | 7 | |a Probability & statistics |2 bicssc | |
| 650 | 7 | |a Cybernetics & systems theory |2 bicssc | |
| 653 | |a System Identification | ||
| 653 | |a Machine Learning | ||
| 653 | |a Linear Dynamical Systems | ||
| 653 | |a Nonlinear Dynamical Systems | ||
| 653 | |a Kernel-based Regularization | ||
| 653 | |a Bayesian Interpretation of Regularization | ||
| 653 | |a Gaussian Processes | ||
| 653 | |a Reproducing Kernel Hilbert Spaces | ||
| 653 | |a Estimation Theory | ||
| 653 | |a Support Vector Machines | ||
| 653 | |a Regularization Networks | ||
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| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/84390 |7 0 |z DOAB: description of the publication |
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