Year: 1986
Type: conference-abstract
Abstract: Vector quantization (VQ) is the coding or mapping of continuous or high-resolution vectors into a finite rate digital representation. The general goal is either analog-to-digital conversion or data compression with a minimum loss of fidelity. In this paper, the basic vector quantizer structures and code design techniques for fixed rate vector quantizers are surveyed and applications to speech coding and recognition are described.
DOI: 10.1121/1.2023758
Author: Robert M. Gray
Institution: Stanford University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2092989265