Object oriented learning network and its applications

Author

Hu, Jinglu ; Hirasawa, Kotaro

Author_Institution

Dept. of Electr. & Electron. Syst. Eng., Kyushu Univ., Fukuoka, Japan

Volume

2

fYear

1999

fDate

36342

Firstpage

1298

Abstract

Introduces a scheme to construct object oriented learning networks (OOLN). The idea is to construct a learning network with two levels. The high-level network is built based on application specific prior knowledge such that it has a structure favorable to the applications. The low-level one consists of a class of conventional neural networks. The OOLN is expected to have both application flexibility and representation flexibility

Keywords

adaptive control; control system synthesis; fuzzy set theory; learning (artificial intelligence); neurocontrollers; nonlinear control systems; object-oriented methods; parameter estimation; prediction theory; radial basis function networks; application flexibility; high-level network; low-level network; object oriented learning network; representation flexibility; Biological system modeling; Computer networks; Control system synthesis; Differential equations; Neural networks; Nonlinear control systems; Nonlinear equations; Object oriented modeling; Radial basis function networks; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1999. IJCNN '99. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-5529-6

Type

conf

DOI

10.1109/IJCNN.1999.831149

Filename

831149