Implementing of An Improved Structure Based on Standard ART-2 Neural Network

摘要：

ART-2 is a self-organized and unsupervised artificial neural network which can recognize complicated inputting patterns. This paper presents a new structure aiming to discard small amplitude information during classifying the data by Standard ART-2 network, especially the time series data. So, we proposed an improved structure based on standard ART-2.Finally, the problem of discard small amplitude information1 is successfully resolved by improved structure and a simulation is given to show the superiority.

关键词： Artificial Neural Network ART-2 small amplitude information

作者: Guoli Gao Hongjun Chen

作者单位: Department of Information Engineering,Jilin Agricultural Science and Technology College Jilin, China Department of Electrical Engineering, Jilin Railway Vocational and Technology College Jilin, China

会议类型: 国际会议

会议名称: 2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

会议地点: 长春

会议语种:英文

页码: 58-60

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）