Presentation | 1994/11/29 The Relationship between the Probability Density of Input Signals and the Reference Vector Distribution in a Modified Kohonen's Model Kouji Kurata, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | It is a property common to the models of self-organizing topographic mapping to assign more units to the signals which they learn more frequently than others in order to get higher resolution about such signals.In Kohonen's model,Ritter showed that resolution or the density of units mapped into the signal space is asymptotically proportional,not to the probability density function p of input signals,but to p^2, 3>.In this paper, a class of models will be proposed which contains Kohonen's model as a special case.Within the class,it is possible to design such a model that the density of units is asymptotically proportional to p^δ with any given positive δ.It will be proved that the mapping loses its stability if one tries to make δ negative. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Self-Organizing Map / Reference Vector / Instability / Micro- Structure |
Paper # | NC94-50 |
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Conference Information | |
Committee | NC |
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Conference Date | 1994/11/29(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | The Relationship between the Probability Density of Input Signals and the Reference Vector Distribution in a Modified Kohonen's Model |
Sub Title (in English) | |
Keyword(1) | Self-Organizing Map |
Keyword(2) | Reference Vector |
Keyword(3) | Instability |
Keyword(4) | Micro- Structure |
1st Author's Name | Kouji Kurata |
1st Author's Affiliation | Faculty of Engineering Science,Osaka University() |
Date | 1994/11/29 |
Paper # | NC94-50 |
Volume (vol) | vol.94 |
Number (no) | 377 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |