Random Re-connection Leaning Algorithm of CMAC Model in Prosthetic Knee Control

摘要：

A new learning algorithm of random re-connection (RRC) originating from the problem of mapping precision of CMAC controller used for prosthetic knee, which connects input layer with neural cell layer, is put forward from the view point of structure optimization in this paper. After the learning process of RRC, the in-degree distribution of neural cell becomes to follow power-law, which indicates that the effect of every cell in pattern identification is different. The simulation result of applying the RRC algorithm to prosthesis control shows that the algorithm of random re-connection can significantly improve the mapping precision of CMAC network model.

关键词： CMAC Prosthetic knee LMS algorithm Random re-connection (RRC) Structure optimization

作者: YU Hong-Liu QIAN Xing-San LI Shou-Wei WANG Shuyi SHEN Ling

作者单位: Institute of Biomechanics and Rehabilitation Engineering，University of Shanghai for Science and Tech Institute of Industry Engineering,University of Shanghai for Science and Technology ,516 Jungong Roa School of Business &Administration, Jiangsu University, Zhenjiang, 212013, China

会议类型: 国际会议

会议名称: 第三届IEEE无线通讯、网络技术暨移动计算国际会议

会议地点: 上海

会议语种:英文

在线出版日期: 2007-09-21（万方平台首次上网日期，不代表论文的发表时间）