Competitive learning with subspace search in transform domain

Wen Jyi Hwang; Shi Chiang Liao

doi:10.1049/el:19980858

Competitive learning with subspace search in transform domain

Wen Jyi Hwang^*, Shi Chiang Liao

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

A new competitive learning (CL) algorithm with k-winners-take-all activation is presented. The k winning neurons for updating are those best matching the input vector in the wavelet domain with subspace search. Simulation results show that the algorithm gives a better performance than that of the traditional CL algorithm while requiring much less computational time.

Original language	English
Pages (from-to)	1240-1241
Number of pages	2
Journal	Electronics Letters
Volume	34
Issue number	12
DOIs	https://doi.org/10.1049/el:19980858
Publication status	Published - 1998 Jun 11
Externally published	Yes

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1049/el:19980858

Cite this

@article{61eaf105909b447b84bb9d49a9b6a74a,

title = "Competitive learning with subspace search in transform domain",

abstract = "A new competitive learning (CL) algorithm with k-winners-take-all activation is presented. The k winning neurons for updating are those best matching the input vector in the wavelet domain with subspace search. Simulation results show that the algorithm gives a better performance than that of the traditional CL algorithm while requiring much less computational time.",

author = "Hwang, {Wen Jyi} and Liao, {Shi Chiang}",

year = "1998",

month = jun,

day = "11",

doi = "10.1049/el:19980858",

language = "English",

volume = "34",

pages = "1240--1241",

journal = "Electronics Letters",

issn = "0013-5194",

publisher = "John Wiley & Sons Inc.",

number = "12",

}

TY - JOUR

T1 - Competitive learning with subspace search in transform domain

AU - Hwang, Wen Jyi

AU - Liao, Shi Chiang

PY - 1998/6/11

Y1 - 1998/6/11

N2 - A new competitive learning (CL) algorithm with k-winners-take-all activation is presented. The k winning neurons for updating are those best matching the input vector in the wavelet domain with subspace search. Simulation results show that the algorithm gives a better performance than that of the traditional CL algorithm while requiring much less computational time.

AB - A new competitive learning (CL) algorithm with k-winners-take-all activation is presented. The k winning neurons for updating are those best matching the input vector in the wavelet domain with subspace search. Simulation results show that the algorithm gives a better performance than that of the traditional CL algorithm while requiring much less computational time.

UR - http://www.scopus.com/inward/record.url?scp=0032098167&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032098167&partnerID=8YFLogxK

U2 - 10.1049/el:19980858

DO - 10.1049/el:19980858

M3 - Article

AN - SCOPUS:0032098167

SN - 0013-5194

VL - 34

SP - 1240

EP - 1241

JO - Electronics Letters

JF - Electronics Letters

IS - 12

ER -

Competitive learning with subspace search in transform domain

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this