Vector Quantization I:Structure and Performance
Vector quantization (VQ) is a generalization of scalar quantization to the quantization of a vector, an ordered set of real numbers. The jump from one dimension to multiple dimensions is a major step and allows a wealth of new ideas, concepts, techniques, and applications to arise that often have no counterpart in the simple case of scalar quantization. While scalar quantization is used primarily for analog-to-digital conversion, VQ is used with sophisticated digital signal processing, where in most cases the input signal already has some form of digital representation and the desired output is a compressed version of the original signal. VQ is usually, but not exclusively, used for the purpose of data compression. Nevertheless, there are interesting parallels with scalar quantization and many of the structural models and analytical and design techniques used in VQ are natural generalizations of the scalar case.
KeywordsCovariance Hexagonal Dinates Dmax Rote
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