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Bayesian methodsBayesian / computational

Robust Particle Filter

Den robuste partikelfilter er en sekventiel Monte Carlo-metode, der sporer skjulte tilstande i ikke-lineære, ikke-Gaussiske systemer, samtidig med at den forbliver resistent over for outliers og model-fejlspecificering. Den erstatter den standard Gaussiske likelihood med en tæt-halet eller begrænset-indflydelses-densitet, således at anomale observationer får nedvægtet betydning og ikke kan afspore tilstandsestimatet.

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Kilder

  1. Ristic, B., Arulampalam, S. & Gordon, N. (2004). Beyond the Kalman Filter: Particle Filters for Tracking Applications. Artech House. ISBN: 978-1580536318
  2. Hurzeler, M. & Kunsch, H. R. (1998). Monte Carlo approximations for general state-space models. Journal of Computational and Graphical Statistics, 7(2), 175-193. link

Sådan citerer du denne side

ScholarGate. (2026, June 3). Robust Particle Filter. ScholarGate. https://scholargate.app/da/bayesian/robust-particle-filter

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ScholarGateRobust Particle Filter (Robust Particle Filter). Hentet 2026-06-15 fra https://scholargate.app/da/bayesian/robust-particle-filter · Datasæt: https://doi.org/10.5281/zenodo.20539026