1 May 1994 Median learning vector quantizer
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In this paper we propose a novel class of learning vector quantizers (LVQ) based on multivariate data ordering. Linear LVQ is not the optimal estimator for non-Gaussian multivariate data distributions. Furthermore, it is not robust either in the case of outliers or in the case of erroneous decisions. The novel LVQs use multivariate ordering in order to obtain location estimators that are robust and that provide superior and, in certain cases, optimal performance for non-Gaussian multivariate distributions. A special case of the novel LVQ class is the marginal median LVQ (MM LVQ), which uses the marginal median as multivariate estimator of location.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ioannis Pitas, P. Kiniklis, "Median learning vector quantizer", Proc. SPIE 2180, Nonlinear Image Processing V, (1 May 1994); doi: 10.1117/12.172566; https://doi.org/10.1117/12.172566


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