Improving dynamic learning vector quantization

Proceedings - International Conference on Pattern Recognition

Volumn 2, Issue , 2006, Pages 804-807

  De Stefano, Claudio ^a   D'Elia, Ciro ^a   Marcelli, Angelo ^b   Di Freca, Alessandra Scotto ^a  

^a UNIVERSITY OF CASSINO AND SOUTHERN LAZIO   (Italy)

^b UNIVERSITY OF SALERNO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; DATABASE SYSTEMS; FEATURE EXTRACTION; VECTOR QUANTIZATION;

DYNAMIC LEARNING VECTOR QUANTIZATION; MACHINE LEARNING REPOSITORY;

LEARNING SYSTEMS;

EID: 34047194623     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2006.699     Document Type: Conference Paper

References (6)

1. T. Kohonen, Self Organizing Map, Springer, Berlin, 1995.
2. S. C. Ahalt et al, "Competitive learning Algorithms for Vector Quantization", Neural Networks, 1990, vol. 3, pp. 277-290.
3. L. Xu, A. Krzyzak, and E. Oja, "Rival penalized competitive learning for clustering analysis, RBF net, and curve detection", IEEE Trans. on Neural Networks, Vol. 4, Issue 4, July 1993, pp. 636-649.
4. C. De Stefano, C. D'Elia, A. Marcelli, "A Dynamic Approach to Learning Vector Quantization", ICPR 2004, Cambridge, UK, 2004, vol. 4, pp. 601-604.
5. T. Kohonen et al "LVQ_PAK: A Program Package for the Correct Application of Learning Vector Quantization Algorithms", Proc. IJCNN, Baltimore, vol. I, 1992, pp. 725-730.
6. B. Yang "Projection approximation subspace tracking"; IEEE Trans. on Signal Processing, Vol. 43, Issue: 1, Jan. 1995, pp.95-107.