A method to obtain better codebooks for vector quantizers than those achieved by the generalized Lloyd algorithm

Author

Yair, Eyal ; Zeger, Kenneth

Author_Institution

IBM Israel Sci. Center, Technion City, Haifa, Israel

fYear

1991

fDate

5-7 Mar 1991

Firstpage

191

Lastpage

194

Abstract

The method is based on a deterministic on-line design technique (similar to the Kohonen learning scheme) which incorporates principles of stochastic relaxation. In contrast to the Kohonen winner-take-all competition between the candidate codevectors, it performs a `soft´ competition where each codevector is assigned a winning score and all codevectors are updated simultaneously according to these scores. A temperature schedule is used to control the speed of convergence versus the quality of the codebook

Keywords

convergence; intelligent design assistants; learning (artificial intelligence); neural nets; online operation; vector quantisation; Kohonen learning scheme; codebooks; deterministic online design; generalized Lloyd algorithm; quality; soft competition; speed of convergence; stochastic relaxation; temperature schedule; vector quantizers; winning score; Algorithm design and analysis; Cities and towns; Convergence; Design methodology; Iterative algorithms; Least squares approximation; Prototypes; Stochastic processes; Temperature control; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Electronics Engineers in Israel, 1991. Proceedings., 17th Convention of

Conference_Location

Tel Aviv

Print_ISBN

0-87942-678-0

Type

conf

DOI

10.1109/EEIS.1991.217666

Filename

217666