EPSRC Reference: |
GR/K69704/01 |
Title: |
PARTICLE APPROXIMATIONS IN NONLINEARFILTERING |
Principal Investigator: |
Lyons, Professor T |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Mathematics |
Organisation: |
Imperial College London |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 October 1995 |
Ends: |
30 September 1998 |
Value (£): |
113,192
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EPSRC Research Topic Classifications: |
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EPSRC Industrial Sector Classifications: |
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Related Grants: |
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Panel History: |
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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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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.imperial.ac.uk |