PARTIAL-DISTORTION-WEIGHTED FUZZY COMPETITIVE LEARNING ALGORITHM FOR VECTOR QUANTIZATION

Authors
ZHU C LI LH WANG TJ HE ZY
Citation
C. Zhu et al., PARTIAL-DISTORTION-WEIGHTED FUZZY COMPETITIVE LEARNING ALGORITHM FOR VECTOR QUANTIZATION, Electronics Letters, 30(6), 1994, pp. 505-506
Citations number
7
Categorie Soggetti
Engineering, Eletrical & Electronic
Journal title
Electronics Letters → ACNP
ISSN journal
00135194
Volume
30
Issue
6
Year of publication
1994
Pages
505 - 506
Database
ISI
SICI code
0013-5194(1994)30:6<505:PFCLAF>2.0.ZU;2-U
Abstract
An effective competitive learning algorithm called the partial-distort ion-weighted fuzzy competitive learning (PDW-FCL) algorithm is develop ed for vector quantisation. The PDW-FCL algorithm is able to minimise the likelihood of neuron (codevector) underuse and make good use of ev ery neuron for optimal vector quantiser design.