DocumentCode
329054
Title
Artificial neuronal group method for data handling
Author
Hu, Shengfa ; Li, Liang ; Yan, Pingfan
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume
2
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
1685
Abstract
In this paper an artificial neuronal group method for data handling (ANGMDH) is proposed. The basic unit of this method, artificial neuronal group or Ivakhnenko polynomial, is implemented by a Sigma-Pi neural network. A simulation for a two joints manipulator hand-eye coordination system shows that this method has the advantage of small samples and high approximating error. It also seldom requires knowledge about parameters of the network.
Keywords
identification; learning (artificial intelligence); manipulators; neural nets; polynomials; Ivakhnenko polynomial; Sigma-Pi neural network; artificial neuronal group method for data handling; high approximating error; small samples; two joints manipulator hand-eye coordination system; Artificial neural networks; Automation; Control theory; Data handling; Input variables; Multi-layer neural network; Neurons; Nonlinear systems; Polynomials; System identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.716977
Filename
716977
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