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Optimisation of digital learning networks when applied to pattern recognition of mass spectra

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2 Author(s)
Stonham, T.J. ; University of Kent at Canterbury, Electronics Laboratories, Canterbury, UK ; Aleksander, I.

A pattern classifier employing n-tuple sampling digital learning networks is analysed to show that redundancy can occur both due to the common occurrence of sets of n-tuples of the sample pattern and invariant points in the patterns. Some experimental results are given for a mass-spectrum classifier, where the system has been optimised by reconnection to reduce this redundancy.

Published in:

Electronics Letters  (Volume:10 ,  Issue: 15 )