Abstract:
This paper deals with a methodfor cleaning up time series data contaminated with the white noise by using wavelet shrinkage. First, data are transformeded to the wavelet domain then data are discriminated using soft-thresholding to the wavelet coeficienfs to .get wavelet shrinkage coeficients. These wavelet shrinkage coefficients are retransform to the time domain and the resuli is expected to be free of the white noise. We conducted some experiments [using 2 sets of data] and the results were satisfactory.
