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《Ordnace Industry Automation》 2002-06
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The Application of Wavelet Analysis in Elimination Noise of Signal

HE Feng-hua (Dept. of Computer, Xi抋n Institute of Science &Technology, Xi抋n 710054, China)  
Based on wavelet analysis, the noise of signal was eliminated with multi-scale wavelet transform and wavelet packet transform. Multi-scale wavelet transform is that the signal was decomposed into high or low frequency elements. The low frequency elements include the main performances of the signal while the high frequency elements consist of more noises, reconstructing the signal can be achieved after flatting the high frequency elements. The three means of constraint, acquiescent threshold value, and given soft/hard threshold value were used to eliminate signal noise. Wavelet packet transform elimination noise is that wavelet packet of the signal was decomposed, and the best wavelet packet base was computed, the threshold value of decomposed coefficients was processed and the original signal was reconstructed, so, elimination noise of signal was realized. A few Matlab elimination noise functions are given such as wavedec and waverec 1-D function of decomposition and reconstruction of multi-scale wavelet, ddencmp function of acquiescent threshold value and wdencmp function of elimination noise, ddencmp and wdencmp function of wavelet packet transform. Experiments show this method has high efficiency and practicality.
【CateGory Index】: TN911.6
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