EPSRC Reference: |
GR/K71370/01 |
Title: |
VALIDATION,COMPLEXITY AND GENERALISATION OF NON-LINEAR SYSTEM IDENTIFICATION |
Principal Investigator: |
Billings, Professor SA |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Automatic Control and Systems Eng |
Organisation: |
University of Sheffield |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
01 October 1995 |
Ends: |
30 September 1998 |
Value (£): |
127,198
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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 traditional approach to model validation has been to statistically test if the residuals are unpredictable and contain no information. This works well if the only objective is to predict future output values. But the aim of many identification studies, including the training of neural networks, is to estimate a description which accurately captures the characteristics and dynamics of the underlying system. These ideas are developed in the present proposal to introduce the new concept of qualitative model validation for nonlinear system identification. These concepts will then be used to enhance statistical model validation methods, to study what aspects of nonlinear identification most influences qualitative model properties, to investigate the choice of sample rate and to considerr the issues of model complexity and generalisation.
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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.shef.ac.uk |