DocumentCode :
389670
Title :
An improved adaptive neural network and its application on random shape
Author :
Mo, Can-Lin ; Tan, Jian-Rong
Author_Institution :
State Key Lab. of CAD & CG, Zhejiang Univ., China
Volume :
1
fYear :
2002
fDate :
2002
Firstpage :
91
Abstract :
The random shape generation method is put forward based on adaptive neural networks. The adaptive neural network is trained from an arbitrary regular geometric shape during the random deformation process. Thus, the regular shape can be changed to an irregular one with the adaptive learning method, and the global and local controllability can both be enhanced. With an improvement on the traditional adaptive neural network algorithm, certainty and randomness can be fully combined, so that fuzzy controllability and adjustability can be dominated easily and concisely.
Keywords :
adaptive control; computational geometry; controllability; neurocontrollers; shape control; adaptive learning method; adaptive neural network; certainty; free shape; fuzzy adjustability; fuzzy controllability; global controllability; local controllability; neural network training; random deformation process; random shape generation method; randomness; Adaptive control; Adaptive systems; Artificial neural networks; Controllability; Fractals; Fuzzy control; Neural networks; Programmable control; Shape control; Solid modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
Type :
conf
DOI :
10.1109/ICMLC.2002.1176716
Filename :
1176716
Link To Document :
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