Fast design algorithm for competitive learning

Wen Jyi Hwang; Faa Jeng Lin; Yi Chong Zeng

doi:10.1049/el:19971010

Fast design algorithm for competitive learning

Wen Jyi Hwang, Faa Jeng Lin, Yi Chong Zeng

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

8 Citations (Scopus)

Abstract

The authors present a new, fast computation algorithm which significantly reduces the training time of the competitive learning (CL) algorithm without sacrificing its performance. The training process is performed in the wavelet domain to identify the winning neural units with a small number of multiplications. Simulation results show that in many cases the algorithm requires < 10% of the computational time required by traditional CL algorithms.

Original language	English
Pages (from-to)	1469-1471
Number of pages	3
Journal	Electronics Letters
Volume	33
Issue number	17
DOIs	https://doi.org/10.1049/el:19971010
Publication status	Published - 1997 Aug 14
Externally published	Yes

Keywords

Learning systems
Neural networks
Wavelet transforms

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1049/el:19971010

Cite this

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title = "Fast design algorithm for competitive learning",

abstract = "The authors present a new, fast computation algorithm which significantly reduces the training time of the competitive learning (CL) algorithm without sacrificing its performance. The training process is performed in the wavelet domain to identify the winning neural units with a small number of multiplications. Simulation results show that in many cases the algorithm requires < 10% of the computational time required by traditional CL algorithms.",

keywords = "Learning systems, Neural networks, Wavelet transforms",

author = "Hwang, {Wen Jyi} and Lin, {Faa Jeng} and Zeng, {Yi Chong}",

year = "1997",

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AU - Zeng, Yi Chong

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N2 - The authors present a new, fast computation algorithm which significantly reduces the training time of the competitive learning (CL) algorithm without sacrificing its performance. The training process is performed in the wavelet domain to identify the winning neural units with a small number of multiplications. Simulation results show that in many cases the algorithm requires < 10% of the computational time required by traditional CL algorithms.

AB - The authors present a new, fast computation algorithm which significantly reduces the training time of the competitive learning (CL) algorithm without sacrificing its performance. The training process is performed in the wavelet domain to identify the winning neural units with a small number of multiplications. Simulation results show that in many cases the algorithm requires < 10% of the computational time required by traditional CL algorithms.

KW - Learning systems

KW - Neural networks

KW - Wavelet transforms

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Fast design algorithm for competitive learning

Abstract

Keywords

ASJC Scopus subject areas

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