DocumentCode
1869811
Title
An improved architecture based on typical ART-2 neural network
Author
Lv, Xiujiang ; Yao, Guangshun ; Zhao, Yan ; Zhang, Qiwen ; Li, Yu´e ; Wang, Ning
Author_Institution
Dept. of Electron. & Electr. Eng., Changchun Univ. of Technol.
fYear
2006
fDate
19-21 Jan. 2006
Lastpage
1121
Abstract
ART-2 is a self-organized and unsupervised artificial neural network constructed from adaptive resonance theory which can be used to classify continuous active data. But we found that the network has just used the big amplitude information during classifying the data by typical ART-2 network, especially the time series data. Therefore, we proposed an improved architecture based on typical ART-2. Then, we point out the superiority of improved ART-2 network over typical ART-2 network in theory. At last, a simulation is given to show the superiority
Keywords
adaptive resonance theory; neural nets; time series; unsupervised learning; ART-2 neural network; adaptive resonance theory; self-organized neural network; time series data; unsupervised artificial neural network; Adaptive filters; Adaptive systems; Artificial neural networks; Electronic mail; Feedback loop; Neural networks; Neurofeedback; Neurons; Resonance; Subspace constraints;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on
Conference_Location
Harbin
Print_ISBN
0-7803-9395-3
Type
conf
DOI
10.1109/ISSCAA.2006.1627563
Filename
1627563
Link To Document