It is often reported in the technique literature that the success of the self-organizing feature map (SOM) formation is critically dependent on the initial weights and the selection of main parameters of the algorithm, namely, the learning-rate parameter and the neighborhood set. In this paper, we propose a healing mechanism to repair feature maps that are not well topologically ordered. The healed map is then further fine-tune by the SOM algorithm so as to improve the accuracy of the map. Two data sets are tested to illustrate the performance of the proposed method.
|Number of pages||6|
|State||Published - 2000|
|Event||International Joint Conference on Neural Networks (IJCNN'2000) - Como, Italy|
Duration: 24 Jul 2000 → 27 Jul 2000
|Conference||International Joint Conference on Neural Networks (IJCNN'2000)|
|Period||24/07/00 → 27/07/00|