Title :
Competitive splitting for codebook initialization
Author :
Xiong, Huilin ; Swamy, M.N.S. ; Ahmad, M.O.
Author_Institution :
Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada
fDate :
5/1/2004 12:00:00 AM
Abstract :
Codebook initialization usually has a significant effect on the performance of vector quantization algorithms. This letter presents a new scheme of codebook initialization in which the competitive learning and code vector splitting are incorporated together to produce a good initial codebook. Based mainly on the geometrical measurements of the learning tracks of the code vectors, the competitive splitting mechanism shows an ability to appropriately allocate code vectors according to the spatial distribution of the input data and, therefore, tends to give a better initial codebook. Comparisons with other initialization techniques demonstrate the effectiveness of the new scheme.
Keywords :
unsupervised learning; vector quantisation; code vector splitting; codebook initialization; competitive learning; initialization technique; spatial distribution; vector quantization algorithms; Algorithm design and analysis; Clustering algorithms; Communication system control; Councils; Learning systems; Process control; Signal processing; Signal processing algorithms; Vector quantization;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2004.824054