Linde–Buzo–Gray algorithm
The Linde–Buzo–Gray algorithm (introduced by Yoseph Linde, Andrés Buzo and Robert M. Gray in 1980) is a vector quantization algorithm to derive a good codebook.
It is similar to the k-means method in data clustering.

The Linde–Buzo–Gray algorithm (introduced by Yoseph Linde, Andrés Buzo and Robert M. Gray in 1980) is a vector quantization algorithm to derive a good codebook.

It is similar to the k-means method in data clustering.

The algorithm[edit]

At each iteration, each vector is split into two new vectors.

  • A initial state: centroid of the training sequence;
  • B initial estimation #1: code book of size 2;
  • C final estimation after LGA: Optimal code book with 2 vectors;
  • D initial estimation #2: code book of size 4;
  • E final estimation after LGA: Optimal code book with 4 vectors;

References[edit]

External links[edit]

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Machine Learning Methods & Algorithms »Machine Learning Methods & Algorithms
Unsupervised learning »Unsupervised learning
Vector quantization (VQ) »Vector quantization (VQ)
Linde–Buzo–Gray algorithm
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