Approximate Bayesian recursive estimation

Bayesian learning provides a firm theoretical basis of the design and exploitation of algorithms in data-streams processing (preprocessing, change detection, hypothesis testing, clustering, etc.). Primarily, it relies on a recursive parameter estimation of a firmly bounded complexity. As a rule, it...

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Veröffentlicht in:	Information sciences 2014-11, Vol.285, p.100-111
1. Verfasser:	Karny, Miroslav
Format:	Artikel
Sprache:	eng
Schlagworte:	Approximate parameter estimation Approximation Bayesian analysis Bayesian recursive estimation Design engineering Errors Estimators Forgetting Kullback–Leibler divergence Mathematical models Recursive
Online-Zugang:	Volltext
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