کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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2576507 | 1561356 | 2007 | 4 صفحه PDF | دانلود رایگان |
Recently, we proposed a modular network SOM (mnSOM) in which each nodal unit of the conventional SOM is replaced by a neural network module. In the mnSOM, the learning algorithm is based on the batch learning SOM for generation of stability mapping, since the on-line algorithm of the SOM depends on initial condition and the scheduling of the neighborhood function. However, when the mnSOM is applied to an autonomous robot or a control system in which the unlabeled episode data are observed from sensors one after another, then the mnSOM should be used with on-line mode. In this paper, we propose an on-line mnSOM algorithm based on Bayesian theory in order to generate a stable map. Moreover, the availability of our proposed algorithm is shown with a result of a simulation.
Journal: International Congress Series - Volume 1301, July 2007, Pages 164–167