Heteroscedastic Gaussian Kernel-Based Topographic Maps
نویسندگان
چکیده
منابع مشابه
Heteroscedastic Gaussian Kernel-Based Topographic Maps
Several learning algorithms for topographic map formation have been introduced that adopt overlapping activa-tion regions, rather than Voronoiregions, usually in the form of kernel functions. We review and introduce a numberof fixed point rules for training homogeneous, heteroscedastic but otherwise radially-symmetric Gaussian kernel-based topographic maps, or kernel topographic...
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Abstract— We develop a number of fixed point rules for training homogeneous, heteroscedastic but otherwise radially-symmetric Gaussian kernel-based topographic maps. We extend the batch map algorithm to the heteroscedastic case and introduce two candidates of fixed point rules for which the end-states, i.e., after the neighborhood range has vanished, are identical to the maximum likelihood Gaus...
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A crucial issue when applying topographic maps for clustering purposes is how to select the map’s overall degree of smoothness. In this paper, we develop a new strategy for optimally smoothing, by a common scale factor, the density estimates generated by Gaussian kernel-based topographic maps. We also introduce a new representation structure for images of shapes, and a new metric for clustering...
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ژورنال
عنوان ژورنال: Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
سال: 2007
ISSN: 1347-7986,1881-7203
DOI: 10.3156/jsoft.19.6_627