Recursive Bayesian Algorithm for Identification of Systems with Non-uniformly Sampled Input Data

To identify systems with non-uniformly sampled input data, a recursive Bayesian identification algorithm with covariance resetting is proposed. Using estimated noise transfer function as a dynamic filter, the system with colored noise is transformed into the system with white noise. In order to impr...

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Veröffentlicht in:	Machine intelligence research (Print) Jg. 15; H. 3; S. 335 - 344
Hauptverfasser:	Jing, Shao-Xue, Pan, Tian-Hong, Li, Zheng-Ming
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Beijing Springer Nature B.V 01.06.2018
Schlagworte:	Algorithms Automation Bayesian analysis Covariance Estimates Identification Kalman filters Parameter estimation Transfer functions White noise
ISSN:	2153-182X, 2153-1838
Online-Zugang:	Volltext
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