Title :
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
fDate :
27 Jun-2 Jul 1994
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;
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
DOI :
10.1109/ICNN.1994.374261