A state-space approach to modeling functional time series: Application to rail supervision - Archive ouverte HAL
Communication Dans Un Congrès Année : 2014

A state-space approach to modeling functional time series: Application to rail supervision

Résumé

This article introduces a state-space model for the dynamic modeling of curve sequences within the framework of railway switches online monitoring. In this context, each curve has the peculiarity of being subject to multiple changes in regime. The proposed model consists of a specific latent variable regression model whose coefficients are supposed to evolve dynamically in the course of time. Its parameters are recursively estimated across a sequence of curves through an online Expectation-Maximization (EM) algorithm. The experimental study conducted on two real power consumption curve sequences from the French high speed network has shown encouraging results.
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Dates et versions

hal-01060094 , version 1 (02-09-2014)

Identifiants

  • HAL Id : hal-01060094 , version 1

Citer

Allou Same, Hani El Assaad. A state-space approach to modeling functional time series: Application to rail supervision. EUSIPCO - European Signal Processing Conference, Sep 2014, Portugal. 5p. ⟨hal-01060094⟩
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