LimNet-Flexible Learning Network Containing Linear Properties
Jinglu Hu*, Kotaro Hirasawa* and Kousuke Kumamaru**
*Department of Electrical and Electronic Systems Engineering, Kyushu University 6-10-1 Hakozaki, Higashi-ku, Fukuoka 812-8581, Japan
**Department of Control Engineering and Science, Kyushu Institute of Technology 680-4 Kawatsu, lizuka 812, Japan
We propose a flexible learning network of a class of linear models. A nonlinear black box system is transformed into a network of known and unknown nodes (node functions), where a linear model is introduced. Unknown nodes are parameterized using neurofuzzy models. The resulting learning network is interpreted as a linear model network (LimNet) and features useful linear properties and universal approximation ability.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.