| EPSRC Reference: |
GR/M41339/01 |
| Title: |
ROPA: NOVEL METHODS FOR DATA PARTITIONING, CLUSTERING AND STATE SEQUENCE ANALYSIS |
| Principal Investigator: |
Roberts, Professor S |
| Other Investigators: |
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| Department: |
Unknown |
| Organisation: |
Imperial College London |
| Scheme: |
ROPA |
| Starts: |
04 March 1999 |
Ends: |
30 September 1999 |
Value (£): |
25,538
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| EPSRC Research Topic Classifications: |
| Information & Knowledge Mgmt |
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| No relevance to Underpinning Sectors |
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Summary on Grant Application Form |
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Data analysis often requires the breaking down of information into stable states or generators of the data. Traditionally the unknown structures in the data are assumed Gaussian distributed. Such methods fail, however, to detect structures which do not have hyper-ellipsodial shape. This project aims to build on our successful work in non-parametric cluster analysis and concentrates on the use of information -theoretic approaches to data partitioning. We also propose to extend such methods of static pattern analysis to the dynamic regime, where for example, transitions between data structures in a time series mat be modelled
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.imperial.ac.uk |