Parameter identification of stochastic diffusion systems with unknown boundary conditions

ShinIchi Aihara, Arunabha Bagchi

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    Abstract

    This paper treats the filtering and parameter identification for the stochastic diffusion systems with unknown boundary conditions. The physical situation of the unknown boundary conditions can be found in many industrial problems,i.g., the salt concentration model of the river Rhine is a typical example . After formulating the diffusion systems by regarding the noisy observation data near the systems boundary region as the system’s boundary inputs, we derive the Kalman filter and the related likelihood function. The consistency property of the maximum likelihood estimate for the systems parameters is also investigated. Some numerical examples are demonstrated.
    Original languageUndefined
    Place of PublicationEnschede
    PublisherUniversity of Twente, Department of Applied Mathematics
    Number of pages34
    Publication statusPublished - Dec 2013

    Publication series

    NameMemorandum
    PublisherUniversity of Twente, Department of Applied Mathematics
    No.2022
    ISSN (Print)1874-4850
    ISSN (Electronic)1874-4850

    Keywords

    • METIS-300216
    • Filtering
    • IR-88244
    • EWI-24097
    • Unknown boundary conditions
    • Stochastic partial differential equations
    • Parameter identification
    • MSC-93E12
    • MSC-93E11
    • MSC-60H15

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