Title :
Signal waveform restoration by wavelet denoising
Author :
Wu, S.Q. ; Ching, P.C.
Author_Institution :
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Abstract :
In this paper, we first establish an approximated sampling theorem for an arbitrary continuous signal which is essential for wavelet analysis. The differences and similarities between quadrature mirror filter decomposition and wavelet decomposition are contrasted. We then propose an efficient way to recover a source signal buried in white noise by using wavelet denoising. The method is capable of reducing the mean square error bound from O(log2(n)) to O(log(n)), where n is the number of samples. It is also shown that the new estimator is asymptotically unbiased if the source signal is a piece-wise polynomial
Keywords :
piecewise polynomial techniques; signal restoration; signal sampling; waveform analysis; wavelet transforms; white noise; approximated sampling theorem; arbitrary continuous signal; mean square error bound; piece-wise polynomial; quadrature mirror filter decomposition; signal waveform restoration; source signal; wavelet analysis; wavelet decomposition; wavelet denoising; white noise; Continuous wavelet transforms; Filters; Mean square error methods; Mirrors; Noise reduction; Sampling methods; Signal analysis; Signal restoration; Wavelet analysis; White noise;
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Paris
Print_ISBN :
0-7803-3512-0
DOI :
10.1109/TFSA.1996.546693
