DocumentCode :
1161562
Title :
Comments on "On a novel unsupervised competitive learning algorithm for scalar quantization"
Author :
Andrew, L.L.H.
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Volume :
7
Issue :
1
fYear :
1996
Firstpage :
254
Lastpage :
256
Abstract :
This note propose an alternative to a neural network for designing scaler quantizers proposed by Van Hulle and Martinez (ibid., vol.5, p.498-501, May 1994). It also points out that the performance measure used is of limited applicability.
Keywords :
neural nets; quantisation (signal); unsupervised learning; neural network; scalar quantization; unsupervised competitive learning algorithm; Algorithm design and analysis; Australia; Backpropagation algorithms; Entropy; Neural networks; Partitioning algorithms; Quantization; Scholarships; Statistics; Training data;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/72.478412
Filename :
478412
Link To Document :
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