Generalized Vander Lugt correlator as an optical pattern classifier and its optimal learning rate

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Generalized Vander Lugt correlator (GVLC) that employs fractional Fourier transforms is an extention of the conventional Vander Lugt correlator. Like neural networks, the error backpropagation algorithm provides the learning rule by which the filter values are changed iteratively to minimize the given error function. We apply the GVLC to pattern classification and develop the optimal learning rate in order to improve the learning convergence and the classification performance. (C) 2002 Published by Elsevier Science B.V.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2002-05
Language
English
Article Type
Article
Keywords

FRACTIONAL FOURIER-TRANSFORM; ORDER

Citation

OPTICS COMMUNICATIONS, v.206, no.1-3, pp.19 - 25

ISSN
0030-4018
URI
http://hdl.handle.net/10203/10961
Appears in Collection
EE-Journal Papers(저널논문)
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