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Robustness of the nonlinear filter

Author

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  • Bhatt, Abhay G.
  • Kallianpur, G.
  • Karandikar, Rajeeva L.

Abstract

In the nonlinear filtering model with signal and observation noise independent, we show that the filter depends continuously on the law of the signal. We do not assume that the signal process is Markov and prove the result under minimal integrability conditions. The analysis is based on expressing the nonlinear filter as a Wiener functional via the Kallianpur-Striebel Bayes formula.

Suggested Citation

  • Bhatt, Abhay G. & Kallianpur, G. & Karandikar, Rajeeva L., 1999. "Robustness of the nonlinear filter," Stochastic Processes and their Applications, Elsevier, vol. 81(2), pages 247-254, June.
    • Handle: RePEc:eee:spapps:v:81:y:1999:i:2:p:247-254
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    Cited by:

    1. Kouritzin, Michael A. & Long, Hongwei & Sun, Wei, 2004. "Markov chain approximations to filtering equations for reflecting diffusion processes," Stochastic Processes and their Applications, Elsevier, vol. 110(2), pages 275-294, April.
    2. Nappo, Giovanna & Torti, Barbara, 2006. "Continuous time random walks and queues: Explicit forms and approximations of the conditional law with respect to local times," Stochastic Processes and their Applications, Elsevier, vol. 116(4), pages 585-610, April.

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    Keywords

    Nonlinear filtering Robustness;

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