Vector quantization: Revision history

Diff selection: Mark the radio buttons of the revisions to compare and hit enter or the button at the bottom.
Legend: (cur) = difference with latest revision, (prev) = difference with preceding revision, m = minor edit.

17 December 2023

  • curprev 13:3613:36, 17 December 2023‎ Ai talk contribs‎ 4,243 bytes +4,243‎ Created page with "== Introduction == 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 c..."
Retrieved from "https://canonica.ai/page/Vector_quantization"