DocumentCode
2861202
Title
Hierarchical artificial neural network architecture
Author
Speer, R.K. ; Moore, W.E.
Author_Institution
Sch. of Inf. Technol., Charles Sturt Univ., Bathurst, Qld., Australia
Volume
3
fYear
1998
fDate
4-9 May 1998
Firstpage
2146
Abstract
This paper presents a hierarchical artificial neural network (HANN) architecture which is shown to be superior to the traditional three layer feedforward neural network for the neurocontrol of mobile robots in terms of robustness and adaptability with implications for application areas other than robotics
Keywords
backpropagation; feedforward neural nets; mobile robots; neural net architecture; neurocontrollers; stability; adaptability; backpropagation; hierarchical neural network; mobile robots; neurocontrol; robustness; Artificial neural networks; Control systems; Information technology; Intelligent control; Intelligent robots; Mobile robots; Neurons; Robot control; Robustness; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location
Anchorage, AK
ISSN
1098-7576
Print_ISBN
0-7803-4859-1
Type
conf
DOI
10.1109/IJCNN.1998.687192
Filename
687192
Link To Document