EPSRC Reference: |
EP/F023049/1 |
Title: |
WORKSHOP: Stochastic Filtering and Control |
Principal Investigator: |
Jacka, Professor SD |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Statistics |
Organisation: |
University of Warwick |
Scheme: |
Standard Research |
Starts: |
10 August 2007 |
Ends: |
09 November 2007 |
Value (£): |
15,962
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EPSRC Research Topic Classifications: |
Statistics & Appl. Probability |
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EPSRC Industrial Sector Classifications: |
No relevance to Underpinning Sectors |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
Advances in probability theory, the increase in computing power that made new computational algorithms possible and important modern applications from statistical signal processing, engineering and mathematical finance have renewed interest in the fields of stochastic filtering and stochastic control. During the last few years, there has been important progress in both their theory and practice. In stochastic filtering, the goal is to estimate a random process from partial (possibly noisy) observations. Applications are widespread, such as missile tracking and handwriting recognition. In the last few years, the field has seen dramatic progress, mainly due to the discovery of a new set of powerful algorithms (sequential Monte Carlo methods or Particle Filters). These new algorithms and the discovery of an error in a forty-year-old proof also renewed interest in the old problem of asymptotic stability, i.e. how the quality of the estimation depends on the initialisation of the algorithm.In stochastic control, the goal is to optimally control a process in order to minimize a risk function or, equivalently, to maximise a utility function. Such problems come up in most fields of engineering, from structural to financial engineering. Recently, however, a huge stimulus to the further development in stochastic control was the discovery of new applications to mathematical finance, which was followed by the discovery of many new mathematical tools created to deal with the new application.We aim to bring together leading researchers working on different aspects of these fields / theory, algorithms or applications / and from both fields of stochastic filtering and stochastic control, which are closely related (for example, in control of partially observed processes). We hope that this will give a fuller picture of the progress that has been made and the challenges that still lie ahead. We believe that there is a significant opportunity for cross-fertilization between the different areas.
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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.warwick.ac.uk |