Moderate deviations for particle filtering

DOI10.1214/105051604000000657zbMath1072.60018arXivmath/0401058OpenAlexW3102792514MaRDI QIDQ1774189

Jamal Najim, Randal Douc, Arnaud Guillin

Publication date: 29 April 2005

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0401058

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Signal detection and filtering (aspects of stochastic processes) (60G35) Large deviations (60F10)

Related Items

Moderate deviation principle for stochastic reaction-diffusion systems with multiplicative noise and non-Lipschitz reaction, Moderate deviation principles for importance sampling estimators of risk measures, Long-term stability of sequential Monte Carlo methods under verifiable conditions

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Sur les déviations modérées des sommes de variables aléatoires vectorielles indépendantes de même loi. (On moderate deviations of sums of independent and identically distributed vector valued random variables)
• Central limit theorem for nonlinear filtering and interacting particle systems
• Large deviations, moderate deviations and LIL for empirical processes
• Large deviations for interacting particle systems: Applications to non-linear filtering
• Moderate deviations of dependent random variables related to CLT
• Sequential Monte Carlo Methods in Practice
• Moderate Deviations and Associated Laplace Approximations for Sums of Independent Random Vectors
• Likelihood analysis of non-Gaussian measurement time series
• Nonlinear filtering: Interacting particle resolution
• Particle approximations of Lyapunov exponents connected to Schrödinger operators and Feynman–Kac semigroups
• Convergence of empirical processes for interacting particle systems with applications to nonlinear filtering
• Large and moderate deviations for estimators of quadratic variational processes of diffusions.
• On the stability of interacting processes with applications to filtering and genetic algorithms
• The Monte-Carlo method for filtering with discrete-time observations