Study on Wavelet Energy Entropy and its Application to Bioelectrical Signal De-noising
Bioelectrical Signal is a weak signal which is buried in the noisy environment, how to recover the weak signal in a strong noisy environment is very important. The paper gets SEMG and EEG as examples, and proposes a de-noising method based on wavelet energy entropy to Bioelectrical Signal de-noising. First multi-scale wavelet decomposition of Bioelectrical Signal is performed by discrete wavelet transform; To calculate the intervals wavelet energy entropy at every decomposed scales, and the filtering value threshold of high-frequency coefficients can be determined by the wavelet energy entropys distribution character; Finally, the de-noised Bioelectrical Signal is obtained by the wavelet reconstructed from the remain low-frequency coefficients and the high-frequency coefficients which are processed. The method has the advantage of setting threshold value adaptively and easily to operate. The experiments show that the method based on wavelet energy entropy has good performance in de-noising, and reserving the detailed information.
Bioelectrical Signal Wavelet transform Wavelet energy entropy De-noising
LUO Zhi-zeng ZHOU Wei
Robot Research Institute Hangzhou Dianzi University,Hangzhou,China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）