This paper proposes an alternative adjustment of weights for Kohonen learning that provides a better match of topology and an improved representation of the input data. Based on the adjustment of weights, a new weighted energy function is defined. Then we propose a new scheme that applies the multiple training concept to the weighted energy function. The new scheme results in a better directional adjustment of weights and increases the training speed of the network dramatically. Finally experimental results demonstrate that much better recognition rate is obtained.
|頁（從 - 到）||747-751|
|期刊||Proceedings of the IEEE International Conference on Systems, Man and Cybernetics|
|出版狀態||已出版 - 1996|
|事件||Proceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics - Beijing, China|
持續時間: 14 10月 1996 → 17 10月 1996