An Analysis of Hardware Configurations for an Adaptive Weightless Neural Network

Lorrentz, Pierre and Howells, Gareth and McDonald-Maier, Klaus D. (2008) An Analysis of Hardware Configurations for an Adaptive Weightless Neural Network. In: Ao, S.I. and Gelman, Len and Hukins, David W.L. and Hunter, Andrew and Korsunsky, A.M., eds. World Congress on Engineering 2008. Lecture Notes in Engineering and Computer Science , I-II. IAE, INT ASSOC ENGINEERS-IAENG, UNIT1, 1-F, 37-39 HUNG TO ROAD, KWUN TONG, HONG KONG, 00000, PEOPLES R CHINA pp. 66-71. ISBN 978-988-98671-9-5 . (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)

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This paper examines the potential offered by adaptive hardware configurations of a class of weightless neural architecture called the Enhanced Probabilistic Convergent Network targeted on a Virtex-II pro FPGA which is re configurable. The reconfiguration and adaptive capability of the Enhanced Probabilistic Convergent Network is a highly adaptive architecture offering a very fast, automated uninterrupted responses in potentially electronically harsh and isolated conditions. The hardware architecture is tested on a benchmark of unconstrained handwritten numerals from the Centre of Excellence for Document Analysis and Recognition.

Item Type: Conference or workshop item (Paper)
Additional information: World Congress on Engineering 2008 Imperial Coll London, London, ENGLAND, JUL 02-04, 2008
Uncontrolled keywords: adaptive neural network; FPGA; handwritten characters; reconfiguration
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.87 Neural computers, neural networks
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Image and Information Engineering
Depositing User: J. Harries
Date Deposited: 18 Apr 2009 11:39
Last Modified: 13 Jun 2014 14:15
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