Performance analysis of LVQ algorithms: a statistical physics approach

Ghosh A, Biehl M, Hammer B (2006)
Neural Networks 19(6-7): 817-829.

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Ghosh A, Biehl M, Hammer B. Performance analysis of LVQ algorithms: a statistical physics approach. Neural Networks. 2006;19(6-7):817-829.
Ghosh, A., Biehl, M., & Hammer, B. (2006). Performance analysis of LVQ algorithms: a statistical physics approach. Neural Networks, 19(6-7), 817-829.
Ghosh, A., Biehl, M., and Hammer, B. (2006). Performance analysis of LVQ algorithms: a statistical physics approach. Neural Networks 19, 817-829.
Ghosh, A., Biehl, M., & Hammer, B., 2006. Performance analysis of LVQ algorithms: a statistical physics approach. Neural Networks, 19(6-7), p 817-829.
A. Ghosh, M. Biehl, and B. Hammer, “Performance analysis of LVQ algorithms: a statistical physics approach”, Neural Networks, vol. 19, 2006, pp. 817-829.
Ghosh, A., Biehl, M., Hammer, B.: Performance analysis of LVQ algorithms: a statistical physics approach. Neural Networks. 19, 817-829 (2006).
Ghosh, A., Biehl, M., and Hammer, Barbara. “Performance analysis of LVQ algorithms: a statistical physics approach”. Neural Networks 19.6-7 (2006): 817-829.
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2 Citations in Europe PMC

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Window-based example selection in learning vector quantization.
Witoelar AW, Ghosh A, de Vries JJ, Hammer B, Biehl M., Neural Comput 22(11), 2010
PMID: 20804387
Adaptive relevance matrices in learning vector quantization.
Schneider P, Biehl M, Hammer B., Neural Comput 21(12), 2009
PMID: 19764875

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