Abstract
When processing signal data with a digital computer one is always faced with the problem that this data on the one hand needs to be stored as compactly as possible and on the other hand must be represented with sufficient accuracy. As digital representations are necessarily always also finite, it is, therefore, the goal of a so-called vector quantizer to map vectors from the input data space onto a finite set of typical reproduction vectors. Through this mapping ideally no information should be lost which is relevant for the further processing of the data. Therefore, one tries to reduce the effort for storage and transmission of vector-valued data by eliminating redundant information contained therein.
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4.5 Bibliographical Remarks
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(2008). Vector Quantization. In: Markov Models for Pattern Recognition. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71770-6_4
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DOI: https://doi.org/10.1007/978-3-540-71770-6_4
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