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Novel Technique To Combine Bws And Fws Classifiers

Lam, K.P., Horne, E. (1993) Novel Technique To Combine Bws And Fws Classifiers. Electronics Letters, 29 (19). pp. 1702-1704. ISSN 0013-5194. (doi:10.1049/el:19931132) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:22174)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1049/el:19931132

Abstract

A novel approach to combining the binary weighted and frequency weighted schemes (BWS and FWS) for pattern classification is described. The method presented employs a well established statistical procedure and offers good performance. The principal advantages of the technique are that only a single layer is required and it avoids the serious problem of choosing optimal values for the zero-frequency components which occur in the FWS. Preliminary experiments demonstrate that the choice of operational parameters required is straightforward. Furthermore, the technique is intrinsically parallel and lends itself naturally to parallel implementation.

Item Type: Article
DOI/Identification number: 10.1049/el:19931132
Uncontrolled keywords: Neural networks, Pattern recognition
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: M. Nasiriavanaki
Date Deposited: 25 Jul 2009 19:57 UTC
Last Modified: 16 Nov 2021 10:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/22174 (The current URI for this page, for reference purposes)

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