Abstract The adaptive stochastic filtering problem for Gaussian processes is considered. The selftuning-synthesis procedure is used to derive two algorithms for this problem. Almost sure convergence for the parameter estimate and the filtering error will be established. The convergence analysis is based on an almost-supermartingale convergence lemma that allows a stochastic Lyapunov like approach.


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    Title :

    Adaptive stochastic filtering problems — The continuous time case


    Contributors:


    Publication date :

    1982-01-01


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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