| EPSRC Reference: |
GR/K07195/01 |
| Title: |
CLIFFORD NETWORKS:NOVEL NEURAL ARCHITECTURES FOR MULTIDIMENSIONAL DATA |
| Principal Investigator: |
Fairhurst, Professor MC |
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| Department: |
Sch of Engineering & Digital Arts |
| Organisation: |
University of Kent |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 March 1995 |
Ends: |
29 February 1996 |
Value (£): |
54,536
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Summary on Grant Application Form |
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Conventional neural network architectures have been successfully applied to a range of practical classification tasks, but have been shown not to be optimised for the processing of data where data points are multidimensional in nature. The range of practical problems which can be effectively tackled using neural architectures (for example, the processing of colour images) could be significantly enhanced if a neural structure were defined which can efficiently handle such multidimensional data. This proposal seeks to explore the idea of exploiting processing paradigms based on the use of Clifford algebras to define learning algorithms for neural networks.
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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.kent.ac.uk |