Deep Learning and System Identification
Lennart Ljung, Carl R. Andersson, Koen Tiels, Thomas B. Schön
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.
Topics & Concepts
Identification (biology)Computer scienceNonlinear autoregressive exogenous modelFeed forwardArtificial intelligenceDeep learningSystem identificationNonlinear system identificationState spaceMachine learningNonlinear systemArtificial neural networkControl engineeringEngineeringData modelingSoftware engineeringMathematicsPhysicsQuantum mechanicsStatisticsBotanyBiologyControl Systems and IdentificationFault Detection and Control SystemsNeural Networks and Applications