Analysis of a sequential Monte Carlo method for optimization in dynamical systems

DOI10.1016/J.SIGPRO.2009.11.007zbMath1194.94117OpenAlexW2049978658MaRDI QIDQ985495

Joaquín Míguez

Publication date: 6 August 2010

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2009.11.007

zbMATH Keywords

stochastic optimizationnonlinear dynamicsdynamic optimizationsequential Monte Carlononlinear tracking

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (1)

Parallel sequential Monte Carlo for stochastic gradient-free nonconvex optimization

Cites Work

• Fundamentals of stochastic filtering
• A new class of particle filters for random dynamic systems with unknown statistics
• Recursive Monte Carlo filters: algorithms and theoretical analysis
• Sequential Monte Carlo Methods in Practice
• On the optimal and suboptimal nonlinear filtering problem for discrete-time systems
• Target Tracking by Particle Filtering in Binary Sensor Networks
• Probability Inequalities for Sums of Bounded Random Variables
• A survey of convergence results on particle filtering methods for practitioners
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