In this paper, a new Bayes fusion algorithm with the Parzen window method, which introduces the non-parameter estimation method of partition recognition into traditional Bayes fusion criterion, is propose. During the process of fusion, which is a repetitious and iterative process, conditional probability density is continuously modified and learned using the Parzen window method, and the global decision is obtained at the fusion center under the bayes decision criterion. In the practical application, the method has been successfully applied into the temperature fault detection and diagnosis system of hydroelectric simulation system of J. Fengman. The analysis of data indicates that the improved algorithm takes precedence over the traditional Bayes criterion.


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    Titel :

    An improved Bayes fusion algorithm with the Parzen window method


    Beteiligte:
    Gang Wang, (Autor:in) / De-gan Zhang, (Autor:in) / Hai Zhao, (Autor:in)


    Erscheinungsdatum :

    01.01.2002


    Format / Umfang :

    439152 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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