In this paper a neural net model for the tree searched vector quantizer is described. The design of the codebook containing the optimal number of representative vectors, incorporates a tree structure with a modified perceptron neural at each node. The proposed algorithm gives reduction in computation requirement compared to the usual full search and tree-search algorithms and requires less memory than the tree search algorithm. Keywords: Vector Quantization, Percetron neural-net, tree search, codebook
Cite as: Mekuria, F., FjÖllbrant, T. (1991) A neural net model for vector quantization. Proc. 2nd European Conference on Speech Communication and Technology (Eurospeech 1991), 1019-1022, doi: 10.21437/Eurospeech.1991-244
@inproceedings{mekuria91_eurospeech,
author={Fisseha Mekuria and Tore FjÖllbrant},
title={{A neural net model for vector quantization}},
year=1991,
booktitle={Proc. 2nd European Conference on Speech Communication and Technology (Eurospeech 1991)},
pages={1019--1022},
doi={10.21437/Eurospeech.1991-244}
}