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Gauss, Kalman and advances in recursive parameter estimation

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  • Peter C. Young
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    Abstract

    The paper considers how the Kalman filter has influenced the development of recursive parameter estimation since the publication of Rudolf Kalman's seminal article in 1960. It will present a partial review of developments over the past half century and provide a tutorial introduction to the refined instrumental variable approach to the optimal recursive estimation of parameters in both discrete and continuous-time transfer function models. The paper concludes with a case study that shows how recursive parameter estimation and the Kalman filter can be combined in the design and development of a real‐time adaptive forecasting and data assimilation system for flow in river systems. Copyright (C) 2010 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/for.1187
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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 30 (2011)
    Issue (Month): 1 (January)
    Pages: 104-146

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    Handle: RePEc:jof:jforec:v:30:y:2011:i:1:p:104-146

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    Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

    Related research

    Keywords: Kalman filter ; recursive parameter estimation ; adaptive forecasting ;

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