Particle Approximations for a Class of Stochastic Partial Differential Equations

Journal Article · Wed Nov 15 00:00:00 EST 2006 · Applied Mathematics and Optimization

DOI:https://doi.org/10.1007/S00245-006-0872-3· OSTI ID:21064202

Crisan, D. ^[1]

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1. Department of Mathematics, Imperial College London, 180 Queen's Gate (United Kingdom), E-mail: [e-mail]

The paper presents a particle approximation for a class of nonlinear stochastic partial differential equations. The work is motivated by and applied to nonlinear filtering. The new results permit the treatment of filtering problems where the signal noise is no longer independent of the observation noise.

• OSTI ID: 21064202
• Journal Information: Applied Mathematics and Optimization, Vol. 54, Issue 3; Other Information: DOI: 10.1007/s00245-006-0872-3; Copyright (c) 2006 Springer; www.springer-ny.com; Country of input: International Atomic Energy Agency (IAEA); ISSN 0095-4616
• Country of Publication: United States
• Language: English

Related Subjects

71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
APPROXIMATIONS
NOISE
NONLINEAR PROBLEMS
PARTIAL DIFFERENTIAL EQUATIONS
SIGNALS
STOCHASTIC PROCESSES