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Details of Grant 

EPSRC Reference: GR/M41339/01
Title: ROPA: NOVEL METHODS FOR DATA PARTITIONING, CLUSTERING AND STATE SEQUENCE ANALYSIS
Principal Investigator: Roberts, Professor S
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Unknown
Organisation: Imperial College London
Scheme: ROPA
Starts: 04 March 1999 Ends: 30 September 1999 Value (£): 25,538
EPSRC Research Topic Classifications:
Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
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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Organisation Website: http://www.imperial.ac.uk