An Improved adaptive algorithm for wavelet transform and its application

摘要：

An improved adaptive algorithm for wavelet transform based on lifting schemes is proposed,cited to prove determine for Iterative weight of LMS, Applies to the subtle characteristics of the signal recognition, This is the desired signal, noise and interference signals to identify the classification, Experimental results show thatThe genetic optimization algorithm weight update iteration by through the RBF neural network, subband filter are synthesis and decomposition effective.Determine the DOA, Enhance the desired signal power, Effective removal of noise, Signal can be determined, Reconstruction of the signal is more closer to the original signal, Verify the correctness of the adaptive wavelet algorithm.

关键词： Adaptive wavelet Transform Genetic Algorithm RBF Network Optimizes

作者: GuiLin Lu ShaoHong Wang

作者单位: GuangXi University of TechnologyGXUT268 Donghuan Road, LiuZhou,China,545006 Ari Force No.95275 LiuZhou,China

会议类型: 国际会议

会议名称: 2010 2nd IEEE International Conference on Information Management and Engineering(2010年IEEE第二届信息管理与工程国际会议 IEEE ICIME 2010)

会议地点: 成都

会议语种:英文

页码: 1-5

在线出版日期: 2010-04-16（万方平台首次上网日期，不代表论文的发表时间）