Generalised particle filters with Gaussian mixtures
DOI10.1016/j.spa.2015.01.008zbMath1327.60096arXiv1306.0255OpenAlexW2139009383MaRDI QIDQ2348297
Publication date: 11 June 2015
Published in: Stochastic Processes and their Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1306.0255
Gaussian mixturesstochastic partial differential equationparticle filtersZakai equationstochastic filtering\(L^2\)-convergence
Filtering in stochastic control theory (93E11) Signal detection and filtering (aspects of stochastic processes) (60G35) Stochastic partial differential equations (aspects of stochastic analysis) (60H15) Random measures (60G57) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) (L^p)-limit theorems (60F25)
Related Items (2)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking
- Particle filters with random resampling times
- Fundamentals of stochastic filtering
- White noise calculus and nonlinear filtering theory
- Evaluation of Gaussian approximations for data assimilation in reservoir models
- Recursive Bayesian estimation using Gaussian sums
- A Gaussian Sum Approach to Phase and Frequency Estimation
- Mixture Kalman Filters
- Target Tracking by Particle Filtering in Binary Sensor Networks
- Particle Filtering for Partially Observed Gaussian State Space Models
- Gaussian sum particle filtering
- A Kusuoka–Lyons–Victoir particle filter
- On the optimal filtering of diffusion processes
- Nonlinear Bayesian estimation using Gaussian sum approximations
- On the best constant in Marcinkiewicz-Zygmund inequality
This page was built for publication: Generalised particle filters with Gaussian mixtures
