Titlebook: Self-Organizing Maps; Teuvo Kohonen Book 19951st edition Springer-Verlag Berlin Heidelberg 1995 Mathematica.algorithms.artificial neural n

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The Basic SOM,certain spatially interacting neural networks. While being categorizable as a special kind of ., this phenomenon is also related to .. In regression, some simple mathematical function is usually fitted to the distribution of sample values of input data. The “nonparametric regression” considered in t

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Learning Vector Quantization, are . clustering and learning methods, LVQ describes .. On the other hand, unlike in SOM, no neighborhoods around the “winner” are defined during learning in the basic LVQ, whereby also no spatial order of the codebook vectors is expected to ensue.

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Applications,ant sensory signals. On the other hand, in the control of effectors or actuators (muscles, motors, etc.) one often has to coordinate many mutually dependent and redundant signals. In both cases, neural networks can be used to implement the great number of implicitly or otherwise poorly defined trans

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