Perlmutter, Keren O. and Perlmutter, Sharon M. and Effros, Michelle and Gray, Robert M. (1994) An iterative joint codebook and classifier improvement algorithm for finite-state vector quantization. In: Asilomar Conference on Signals, Systems and Computers, 28th, Pacific Grove, CA, 31 October-2 November 1998. IEEE , Piscataway, NJ, pp. 701-705. ISBN 0-8186-6405-3 http://resolver.caltech.edu/CaltechAUTHORS:PERasilo94
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A finite-state vector quantizer (FSVQ) is a multicodebook system in, which the current state (or codebook) is chosen as a function of the previously quantized vectors. The authors introduce a novel iterative algorithm for joint codebook and next state function design of full search finite-state vector quantizers. They consider the fixed-rate case, for which no optimal design strategy is known. A locally optimal set of codebooks is designed for the training data and then predecessors to the training vectors associated with each codebook are appropriately labelled and used in designing the classifier. The algorithm iterates between next state function and state codebook design until it arrives at a suitable solution. The proposed design consistently yields better performance than the traditional FSVQ design method (under identical state space and codebook constraints).
|Item Type:||Book Section|
|Additional Information:||© Copyright 1994 IEEE. Reprinted with permission. This work was supported by the NSF. The authors gratefully acknowledge the assistance of Dr. Pamela C. Cosman.|
|Subject Keywords:||computerized tomography, finite state machines, image classification, iterative methods, lung, vector quantization, source code design|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Archive Administrator|
|Deposited On:||13 Feb 2007|
|Last Modified:||26 Dec 2012 09:31|
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