DocumentCode
1553514
Title
Adaptive combination of PCA and VQ networks
Author
Weingessel, Andreas ; Bischof, Horst ; Hornik, Kurt ; Leisch, Friedrich
Author_Institution
Inst. fur Stat. und Wahrscheinlichkeitstheorie, Tech. Univ. Wien, Austria
Volume
8
Issue
5
fYear
1997
fDate
9/1/1997 12:00:00 AM
Firstpage
1208
Lastpage
1211
Abstract
In this paper we consider the principal component analysis (PCA) and vector quantization (VQ) neural networks for image compression. We present a method where the PCA and VQ steps are adaptively combined. A learning algorithm for this combined network is derived. We demonstrate that this approach can improve the results of the successive application of the individually optimal methods
Keywords
adaptive systems; image coding; learning (artificial intelligence); multilayer perceptrons; statistical analysis; vector quantisation; adaptive combination; image compression; learning algorithm; multilayer perceptron; principal component analysis neural net; vector quantization neural networks; Adaptive systems; Entropy; Error correction; Histograms; Image coding; Image reconstruction; Neural networks; Principal component analysis; Vector quantization; Wavelet analysis;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.623222
Filename
623222
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