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Details of Grant 

EPSRC Reference: GR/K69704/01
Title: PARTICLE APPROXIMATIONS IN NONLINEARFILTERING
Principal Investigator: Lyons, Professor T
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Researcher Co-Investigators:
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Department: Dept of Mathematics
Organisation: Imperial College London
Scheme: Standard Research (Pre-FEC)
Starts: 01 October 1995 Ends: 30 September 1998 Value (£): 113,192
EPSRC Research Topic Classifications:
Mathematical Analysis
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Summary on Grant Application Form
The problem of estimating an unobservable signal process X given the information obtained by observing an associated process Y (a noisy observation) within a certain time window [o,t] has a wide range of applications: Reception and discrimination of radio signals, digital data transmission on telephone lines, detection of radar signals, analysis of seismic data, processing of pictures from spacecraft, analysis of electrocardiogram and electro-encephalogram signals etc. The applications it is essential to provide numerically feasible schemes for estimating the conditional distribution of X. This seems a difficult task and has only been completed for the low-dimensional cases, linear, and Benes filters. We proved recently that arbitrarily good approximations of a sample from the posterior distribution of X can be produced by extending measured valued process ideas.Our aim is to study the convergence of the branching particle systems to the SPDE solution and test the quality of the algorithm.
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Organisation Website: http://www.imperial.ac.uk