(1999) 'Decomposition of interacting features using a Kohonen self-organizing feature map neural network', Engineering Applications of Artificial Intelligence, Vol. 12, pp.59-78.Zulkifliah,S.Meeran, Decomposition of interacting features using a Kohonen self-organizing feature map neural network. ...
5) self-organizing feature map 自组织特征映射 1. The application of self-organizing feature map neural network to logging lithological identification; 自组织特征映射神经网络在测井岩性识别中的应用 2. Application and Analysis of Self-Organizing Feature Map; 自组织特征映射网络的分析与应用 3. ...
The back-propagation (BP) network and the Kohonen self-organizing feature map, selected as the representative types for the supervised and unsupervised artificial neural networks (ANN) respectively, are compared in terms of prediction accuracy in the area of bankruptcy prediction. Discriminant analysis ...
Lee, T CScherson, I D
Teuvo kalevi Kohonen is a famous professor in the Finnish Academy of Sciences. He has made many contributions to the field of artificial neural networks. The most famous one is the self-organizing feature map (SOFM) neural network proposed in 1981.() 点击查看答案手机看题 你可能感兴趣的试题 ...
Applying the region growing to the Kohonen's self-organizing feature map, a non-supervised classifier for remotely sensed imagery data is proposed. If the self-organizing feature map is made large enough, i.e., the size is 50X50 sites, it can be considered as a kind of image itself. ...
(1988). Speaker Recognition Using Kohonen's Self-Organizing Feature Map Algorithm, Abstracts of the First Annual INNS Meeting.Naylor, J., Higgins, A., Li, K.P., Schmoldt, D., Speaker recognition using Kohonen's self-organizing feature map algorithm, Neural Networks , v. 1, pp. 311, ...
van Velzen, G A
and Abidi, S. S. R. (2000). Unsupervised case classification using kohonen "self-organizing feature map" in a case-based reasoning system. In 2000 TENCON Proceedings. Intelligent Systems and Tech- nologies for the New Millennium. IEEE, Piscataway, NJ, USA, volume 2, pages 524-7....
This study dedicates to develop a novel fuzzy neural network for clustering the parts into several families based on the image captured from the vision sensor. The proposed network, which posses the fuzzy inputs as well the fuzzy weights, integrates the self-organizing feature map (SOM) neural...