An Adaptive Lifting Wavelet Transform Method Based on Local Correlation Detection

摘要：

The adaptive wavelet transform has better adaptability to signals local features than normal ones. The definition of interval autocorrelation factors is presented. The local correlation of samples and the local features of original signals can be characterized by them. Under each scale, with the help of the original signals local features, the optimal predictors and updaters of different samples are selected adaptively. Simulation results show that the method can give attention to both the signals smooth parts and the singular parts, and get a better transform result. The method especially adapts to the online preprocessing of signals with more changes of local features.

关键词： lifting wavelet correlation adaptive wavelet transform de-noising method

作者: CAO jianjun ZHANG Peilin REN Guoquan GU Zengfeng

作者单位: Shijiazhuang Mechanical Engineering College, Shijiazhuang, 050003 China Shijiazhuang Mechanical Engineering College, Shijiazhuang, 050003 China;College of Mechanical Engine

会议类型: 国际会议

会议名称: 第七届国际测试技术研讨会

会议地点: 北京

会议语种:英文

在线出版日期: 2007-08-05（万方平台首次上网日期，不代表论文的发表时间）