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- Vector_quantization abstract "Vector quantization (VQ) is a classical quantization technique from signal processing which 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.The density matching property of vector quantization is powerful, especially for identifying the density of large and high-dimensioned data. Since data points are represented by the index of their closest centroid, commonly occurring data have low error, and rare data high error. This is why VQ is suitable for lossy data compression. It can also be used for lossy data correction and density estimation.Vector quantization is based on the competitive learning paradigm, so it is closely related to the self-organizing map model.".
- Vector_quantization wikiPageExternalLink qccpack.sourceforge.net.
- Vector_quantization wikiPageExternalLink YDSPR874.pdf.
- Vector_quantization wikiPageExternalLink vq.html.
- Vector_quantization wikiPageID "47805".
- Vector_quantization wikiPageRevisionID "605606902".
- Vector_quantization hasPhotoCollection Vector_quantization.
- Vector_quantization subject Category:Lossy_compression_algorithms.
- Vector_quantization type Abstraction100002137.
- Vector_quantization type Act100030358.
- Vector_quantization type Activity100407535.
- Vector_quantization type Algorithm105847438.
- Vector_quantization type Event100029378.
- Vector_quantization type LossyCompressionAlgorithms.
- Vector_quantization type Procedure101023820.
- Vector_quantization type PsychologicalFeature100023100.
- Vector_quantization type Rule105846932.
- Vector_quantization type YagoPermanentlyLocatedEntity.
- Vector_quantization comment "Vector quantization (VQ) is a classical quantization technique from signal processing which 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.".
- Vector_quantization label "Quantification vectorielle".
- Vector_quantization label "Vector quantization".
- Vector_quantization label "Vektorquantisierung".
- Vector_quantization label "ベクトル量子化".
- Vector_quantization sameAs Vektorquantisierung.
- Vector_quantization sameAs Aprendizaje_de_cuantificación_vectorial.
- Vector_quantization sameAs Quantification_vectorielle.
- Vector_quantization sameAs ベクトル量子化.
- Vector_quantization sameAs m.0cvl4.
- Vector_quantization sameAs Q612536.
- Vector_quantization sameAs Q612536.
- Vector_quantization sameAs Vector_quantization.
- Vector_quantization wasDerivedFrom Vector_quantization?oldid=605606902.
- Vector_quantization isPrimaryTopicOf Vector_quantization.