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JACIII Vol.3 No.4 pp. 303-311
doi: 10.20965/jaciii.1999.p0303
(1999)

Paper:

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

Received:
September 25, 1998
Accepted:
March 15, 1999
Published:
August 20, 1999
Keywords:
Learning network, Linear model, Prior knowledge, Modeling and identification, Nonlinear system
Abstract

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.

Cite this article as:
Jinglu Hu, Kotaro Hirasawa, and Kousuke Kumamaru, “LimNet-Flexible Learning Network Containing Linear Properties,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.4, pp. 303-311, 1999.
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Last updated on Nov. 25, 2021