Linde-Buzo-Gray algorithm

Linde-Buzo-Gray algorithm

The Linde-Buzo-Gray algorithm is a vector quantization algorithm to derive a good codebook.It is similar to the k-means method in data clustering.

The algorithm

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;

ee also

* Canopy clustering algorithm
* Data clustering
* K-means algorithm
* Lloyd's algorithm
* ELBG - Enhanced LBG

External links

* http://www.data-compression.com/vq.html#lbg
* http://ai.unime.it/~gp/english/clustering_applet/elbg_demo_applet.htm

References

* The original paper describing the algorithm, as an extension to Lloyd's algorithm:Linde, Y., Buzo, A., Gray, R., "An Algorithm for Vector Quantizer Design", IEEE Transactions on Communications, vol. 28, pp. 84-94, 1980. http://ieeexplore.ieee.org/xpls/abs_all.jsp?&arnumber=1094577


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