A Fuzzy ARTMAP Model with Contraction Procedure

摘要：

This paper presents a neural network classifier based on fuzzy ARTMAP with conflict-resolving strategy. The proposed model explicitly resolves overlaps among prototypes of different classes through deploying a contraction procedure in the network, therefore, improving its generalization. Compared with other existing methods, the model has the priority of intuition and no parameter tuning. The performance of the model is evaluated using several benchmark data sets. The comparisons with original fuzzy ARTMAP model and other classifiers indicate that the proposed classifier achieves competitive performance.

作者: Xianglin Meng Zhengzhi Wang

作者单位: College of Mechatronics Engineering and Automation,National University of Defense Technology

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

会议地点: 桂林

会议语种:英文

页码: 1507-1512

在线出版日期: 2009-12-19（万方平台首次上网日期，不代表论文的发表时间）