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Process data de-noising using wavelet transform. (English) Zbl 1028.94008
Summary: The recovery of process information from noisy data (denoising) is studied by investigating the classical solution of the estimation problem first. Next, the effectiveness of wavelet-based algorithms for data recovery is considered. A novel method based on coefficient denoising according to the Wiener-Shrink method of wavelet thresholding is proposed. Simulation results are presented, highlighting the advantages of the de-noising method over the classical approaches based on the mean square error criterion.

MSC:
94A12 Signal theory (characterization, reconstruction, filtering, etc.)
65T60 Numerical methods for wavelets
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