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Bayesian methodsBayesian / computational

Penapis Zarah dengan Ralat Pengukuran

Penapis zarah dengan ralat pengukuran eksplisit ialah algoritma Monte Carlo Sekuensial yang menjejak keadaan tersembunyi bagi sistem dinamik tak linear, tak Gaussian sambil memodelkan hingar dalam pemerhatian secara formal. Populasi sampel rawak berbobot (zarah) mewakili taburan keadaan posterior pada setiap langkah masa, dan fungsi kemungkinan pemerhatian mengukur sejauh mana setiap zarah konsisten dengan ukuran berhingar yang diterima.

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Sumber

  1. Gordon, N. J., Salmond, D. J., & Smith, A. F. M. (1993). Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proceedings F – Radar and Signal Processing, 140(2), 107–113. DOI: 10.1049/ip-f-2.1993.0015
  2. Doucet, A., de Freitas, N., & Gordon, N. (Eds.). (2001). Sequential Monte Carlo Methods in Practice. Springer. ISBN: 978-0387951461

Cara memetik halaman ini

ScholarGate. (2026, June 3). Sequential Monte Carlo Particle Filter with Explicit Measurement Error. ScholarGate. https://scholargate.app/ms/bayesian/particle-filter-with-measurement-error

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ScholarGateParticle Filter with Measurement Error (Sequential Monte Carlo Particle Filter with Explicit Measurement Error). Dicapai 2026-06-15 daripada https://scholargate.app/ms/bayesian/particle-filter-with-measurement-error · Set data: https://doi.org/10.5281/zenodo.20539026