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Adaptation Strength According to Neighborhood Ranking of Self-Organizing Neural Networks
Michiharu MAEDA Hiromi MIYAJIMA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2002/09/01
Print ISSN: 0916-8508
Type of Manuscript: Special Section LETTER (Special Section on Nonlinear Theory and Its Applications)
adaptation, self-organizing neural networks, neighborhood ranking, learning, image coding,
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In this paper we treat a novel adaptation strength according to neighborhood ranking of self-organizing neural networks with the objective of avoiding the initial dependency of reference vectors, which is related to the strength in the neural-gas network suggested by Martinetz et al. The present approach exhibits the effectiveness in the average distortion compared to the conventional technique through numerical experiments. Furthermore the present approach is applied to image data and the validity in employing as an image coding system is examined.