Abstract
Deep learning is a topic of considerable interest today. Since it deals with estimating - or learning - models, there are connections to the area of System Identification developed in the Automatic Control community. Such connections are explored and exploited in this contribution. It is stressed that common deep nets such as feedforward and cascadeforward nets are nonlinear ARX (NARX) models, and can thus be easily incorporated in System Identification code and practice. The case of LSTM nets is an example of NonLinear State-Space (NLSS) models.
Original language | English |
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Pages (from-to) | 1175-1181 |
Number of pages | 7 |
Journal | IFAC-PapersOnLine |
Volume | 53 |
Issue number | 2 |
DOIs | |
Publication status | Published - Nov 2020 |
Event | 21st World Congress of the International Federation of Aufomatic Control (IFAC 2020 World Congress) - Berlin, Germany Duration: 12 Jul 2020 → 17 Jul 2020 Conference number: 21 https://www.ifac2020.org/ |
Keywords
- Model structure
- Bias/variance trade-off
- Model validation
- LSTM
- Cascadeforwardnet
- Deep nets
- Bias/Variance Trade-off