Control of annealing in minimal free energy vector quantization

Author

Dersch, D.R. ; Tavan, P.

Author_Institution

Inst. fur Med. Opt., Ludwig-Maximilians-Univ., Munchen, Germany

Volume

2

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

698

Abstract

We derive conservation laws for minimal free energy clustering and vector quantization that allow one to monitor and control a corresponding annealing process. The controlled stochastic annealing thus obtained yields optimal solutions to that optimization problem, as we illustrate by sample simulations. We prove for the resulting codebooks that the discretization density is proportional to the data density in the limit of dense discretization

Keywords

codes; conservation laws; data reduction; free energy; minimisation; simulated annealing; vector quantisation; annealing control; annealing process monitoring; codebooks; conservation laws; controlled stochastic annealing; data density; dense discretization; discretization density; minimal free energy clustering; minimal free energy vector quantization; optimization; simulations; Annealing; Data analysis; Monitoring; Pattern recognition; Signal analysis; Signal processing; Speech analysis; Speech recognition; Stochastic processes; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374261

Filename

374261