Hardware Implementation Issues of the Neighborhood Mechanism in Kohonen Self Organized Feature Maps

In this paper, we discuss an important problem of the selection of the neighborhood radius in the learning schemes of the Winner Takes Most Kohonen neural network. The optimization of this parameter is essential in case of hardware realization of the network given that the lower values of the radius can result in significant reduction of both the power dissipation and the chip area, even by 40-60% that is important in application of such networks in low power devices. The simulation studies reveal that using large initial values of the neighborhood radius usually is not the most optimal. For a wide range of the training parameters some optimal values, usually small, of the neighborhood radius may be indicated that allow for the minimization of the quantization error.

Published in:
Proceedings of the 12th European Symposium on Artificial Neural Networks (ESANN), 565-570
Presented at:
12th European Symposium on Artificial Neural Networks (ESANN), Bruges, Belgium, April 28-30, 2009

Note: The status of this file is: EPFL only

 Record created 2010-04-19, last modified 2018-03-17

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