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Minimax-Robust Filtering and Finite-Length Robust Predictors

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Book cover Robust and Nonlinear Time Series Analysis

Part of the book series: Lecture Notes in Statistics ((LNS,volume 26))

Abstract

This paper consists basically of two parts. In the first part (Sections 2 and 3) , we consider some aspects of linear filtering under uncertainty about the spectral features of the relevant time series. The second part (Sections 4 and 5), considers a time domain approach to the general problem of filtering under probabilistic uncertainty and applies this general formulation to aspects of the linear filtering problem. Each of these approaches represents a different means for solving the minimax robust filtering problem, and both are applied to the specific problem of robust q-step prediction to illustrate the similarities of the two approaches.

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Author information

Authors and Affiliations

  1. Fachbereich Mathematik, Johann Wolfgang Goethe-Universität Frankfurt/Main, D-6000, Frankfurt/Main 1, Germany

    Jürgen Franke

  2. Coordinated Science Laboratory, University of Illinois, 1101 W. Springfield Avenue, Urbana, Illinois, 61801, USA

    H. Vincent Poor

Authors
  1. Jürgen Franke
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  2. H. Vincent Poor
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Editor information

Editors and Affiliations

  1. Fachbereich Mathematik, Universität Frankfurt, Robert Mayer Str. 6-10, 6000, Frankfurt, Germany

    Jürgen Franke  & Wolfgang Härdle  & 

  2. Department of Statistics, GN-22, University of Washington, Seattle, WA, 98195, USA

    Douglas Martin

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© 1984 Springer-Verlag Berlin Heidelberg

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Franke, J., Poor, H.V. (1984). Minimax-Robust Filtering and Finite-Length Robust Predictors. In: Franke, J., Härdle, W., Martin, D. (eds) Robust and Nonlinear Time Series Analysis. Lecture Notes in Statistics, vol 26. Springer, New York, NY. https://doi.org/10.1007/978-1-4615-7821-5_6

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  • DOI: https://doi.org/10.1007/978-1-4615-7821-5_6

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-96102-6

  • Online ISBN: 978-1-4615-7821-5

  • eBook Packages: Springer Book Archive

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