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Proceedings Paper

Vector quantization by neural network
Author(s): Yu He; Qianren Zhang; Yizheng Ye; Zhong-Rong Li
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Paper Abstract

Vector quantization has been widely used in image encoding systems and speech recognition systems science 1980's. In this paper, three kinds of vector quantization approaches are introduced, which are based on neural networks. The principles of using neural networks to improve the performance of vector quantization are described. Because of high parallel computation, learning function, high fault tolerance and selforganizing capability of neural networks, the performance of vector quantizers is improved.

Paper Details

Date Published: 1 July 1990
PDF: 4 pages
Proc. SPIE 1232, Medical Imaging IV: Image Capture and Display, (1 July 1990); doi: 10.1117/12.18880
Show Author Affiliations
Yu He, Harbin Institute of Technology (China)
Qianren Zhang, Harbin Institute of Technology (China)
Yizheng Ye, Harbin Institute of Technology (China)
Zhong-Rong Li, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 1232:
Medical Imaging IV: Image Capture and Display
Yongmin Kim, Editor(s)

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