Preprint available

[Klaus Obermayer]

Dear connectionists

The following preprint is now available online at:
http://kon.cs.tu-berlin.de/publications/#conference


An annealed self-organizing map for source channel coding

M. Burger, T. Graepel, and K. Obermayer
CS Department, Technical University of Berlin, Berlin, Germany

Abstract:
We derive and analyse robust optimization schemes for noisy vector quantization
on the basis of deterministic annealing. Starting from a cost function for 
central clustering that incorporates distortions from channel noise we develop 
a soft topographic vector quantization algorithm (STVQ) which is based on the 
maximum entropy principle and which performs a maximum-likelihood estimate in 
an expectation-maximization (EM) fashion. Annealing in the temperature 
parameter $\beta$ leads to phase transitions in the existing code vector 
representation during the cooling process for which we calculate critical 
temperatures and modes as a function of eigenvectors and eigenvalues of the 
covariance matrix of the data and the transition matrix of the channel noise.
A whole family of vector quantization algorithms is derived from STVQ, among 
them a deterministic annealing scheme for Kohonen's self-organizing map (SOM). 
This algorithm, which we call SSOM, is then applied to vector quantization of 
image data to be sent via a noisy binary symmetric channel. The algorithm's 
performance is compared to those of LBG and STVQ. While it is naturally 
superior to LBG, which does not take into account channel noise, its results 
compare very well to those of STVQ, which is computationally much more 
demanding.   

(This paper will appear at NIPS97)