Seonglae Chodivides continuous variations into finite levels
takes a feature vector and maps it to the index of the nearest code vector in a codebook
Vector quantization
Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors. It was originally used for data compression. It works by dividing a large set of points (vectors) into groups having approximately the same number of points closest to them. Each group is represented by its centroid point, as in k-means and some other clustering algorithms.
https://en.wikipedia.org/wiki/Vector_quantization
Vector Quantization과 Codebook 개념 정리
이 포스트는 개인적으로 공부한 내용을 정리하고 필요한 분들에게 지식을 공유하기 위해 작성되었습니다. 지적하실 내용이 있다면, 언제든 댓글 또는 메일로 알려주시기를 바랍니다.
https://zerojsh00.github.io/posts/Vector-Quantization/