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Parameter estimation for the piecewice-polynomial mean value trend of a stochastic time series

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Abstract

We consider the problem of mean value trend estimation for a stochastic time series in a mixture with noise. The trend is simulated as a polynomial function of time with parameters changing discontinuously at a random instant. The proposed solution of this problem is based on the optimal nonlinear filtering theory for pulsed Markovian processes. An algorithm for approximate estimation of piesewise-linear trend parameters is devised as an example. The results of numerical simulation of a synthesized algorithm are presented.

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Authors
  1. A. A. Mal’tsev
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  2. O. V. Pol’din
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  3. A. M. Silaev
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Additional information

Lobachevsky State University, Nizhny Novgorod, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 40, No. 11, pp. 1405–1415, November, 1997.

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Mal’tsev, A.A., Pol’din, O.V. & Silaev, A.M. Parameter estimation for the piecewice-polynomial mean value trend of a stochastic time series. Radiophys Quantum Electron 40, 947–954 (1997). https://doi.org/10.1007/BF02676696

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  • DOI: https://doi.org/10.1007/BF02676696

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