## Abstract

We present a method for predicting non-stationary signals generated by a time varying composite source. The method is based on the concept of temporal fuzzy clustering. A fuzzy clustering algorithm is applied to the given part (past+present) of the time series and the calculated clusters and membership matrix are then used to estimate a mixture probability distribution function (PDF) underlying the series. In this way a continuous drift in the series distribution expressed as a drift in the clusters' appearance rate can be estimated. A future PDF can then be predicted by fitting a specific model to the estimated past and future PDF values. This also enables the generation of a minimal-mean-squared-error prediction for a future time series element using the estimated mean value of the predicted PDF.

Original language | English |
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Pages | 329-332 |

Number of pages | 4 |

State | Published - 1 Dec 2001 |

Event | 2001 IEEE Workshop on Statitical Signal Processing Proceedings - Singapore, Singapore Duration: 6 Aug 2001 → 8 Aug 2001 |

### Conference

Conference | 2001 IEEE Workshop on Statitical Signal Processing Proceedings |
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Country/Territory | Singapore |

City | Singapore |

Period | 6/08/01 → 8/08/01 |

## ASJC Scopus subject areas

- Signal Processing