Wavelet-based neural network adaptive filter for sEMG denoising

摘要：

　　For the large computation workload of the adaptive filter algorithm and the low filtering speed of the adaptive filter model based on wavelet transform,a wavelet-based neural network adaptive filter model is constructed in this paper.As the neural network has the capacity of distributed storage and fast self-evolution,Hopfield neural network is used to implement adaptive filtering algorithm LMS,so as to increase the computing speed.The model applied to sEMG signal denoising can achieve a better filtering effect.

关键词： sEMG denoising discrete wavelet transform Hopfield neural network adaptive filter

作者: Wang Jianhui Chen Na Xiao Qian Xu Jianyou Gu Shusheng

作者单位: Key Laboratory of Process Industry Automation, Northeastern University, Ministry of Education,Shenyang 110819, China

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 4259-4264

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）