A self-stabilizing learning rule for minor component analysis |
| |
Authors: | Möller Ralf |
| |
Affiliation: | Computer Engineering Group, Faculty of Technology, Bielefeld University, D-33594 Bielefeld, Germany. moeller@techfak.uni-bielefeld.de |
| |
Abstract: | The paper reviews single-neuron learning rules for minor component analysis and suggests a novel minor component learning rule. In this rule, the weight vector length is self-stabilizing, i.e., moving towards unit length in each learning step. In simulations with low- and medium-dimensional data, the performance of the novel learning rule is compared with previously suggested rules. |
| |
Keywords: | |
本文献已被 PubMed 等数据库收录! |
|