Deep Learning and System Identification
Journal: IFAC-PapersOnLine
•
• Elsevier BV
• ISSN:
2405-8963
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.
Subjects & Keywords
How to Cite this Article
Lennart Ljung A, Carl R. Andersson, Koen Tiels, et al. (2020). "Deep Learning and System Identification". IFAC-PapersOnLine. https://doi.org/10.1016/j.ifacol.2020.12.1329