Building the genetic learning rule for adaptive vector quantization in neural networks

Author

Lee, C.H. ; See, S.K.E.

Author_Institution

Dept. of Comput. Sci., City Polytech. of Hong Kong, Kowloon, Hong Kong

fYear

1994

fDate

22-26 Aug 1994

Firstpage

809

Abstract

We present a new unsupervised learning algorithm by means of incorporating the genetic algorithm idea into the neural networks for adaptive vector quantisation. From the simulations, the model can cluster the noisy data and recall the patterns accurately

Keywords

genetic algorithms; neural nets; unsupervised learning; vector quantisation; adaptive vector quantization; genetic algorithm; genetic learning rule; neural networks; noisy data clustering; patterns; simulations; unsupervised learning algorithm; Adaptive systems; Biological system modeling; Cities and towns; Clustering algorithms; Computational modeling; Computer science; Genetic algorithms; Intelligent networks; Neural networks; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '94. IEEE Region 10's Ninth Annual International Conference. Theme: Frontiers of Computer Technology. Proceedings of 1994

Print_ISBN

0-7803-1862-5

Type

conf

DOI

10.1109/TENCON.1994.369199

Filename

369199

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2391912