Extending the Kalman filter for structured identification of linear and nonlinear systems | Zendy

Matthew C. Best | Zendy; Karol Bogdanski | Zendy

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Extending the Kalman filter for structured identification of linear and nonlinear systems

Author(s) -

Matthew C. Best,

Karol Bogdanski

Publication year - 2017

Publication title -

international journal of modelling identification and control

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.322

H-Index - 29

eISSN - 1746-6180

pISSN - 1746-6172

DOI - 10.1504/ijmic.2017.082952

Subject(s) - nonlinear system , kalman filter , control theory (sociology) , identification (biology) , extended kalman filter , noise (video) , system identification , filter (signal processing) , computer science , linear model , nonlinear system identification , linear system , nonlinear filter , canonical form , noise reduction , black box , mathematics , artificial intelligence , filter design , machine learning , data mining , measure (data warehouse) , biology , control (management) , quantum mechanics , physics , botany , image (mathematics) , mathematical analysis , computer vision , pure mathematics

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