Signal Denoising of MEMS Microstructure Profile

Abstract:

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A new signal-denoising approach based on DT-CWT (Dual-Tree Complex Wavelet Transform) is presented in this paper to extract feature information from microstructure profile. It takes advantage of shift invariance of DT-CWT, non-Gaussian probability distribution for the wavelet coefficients and the statistical dependencies between a coefficient and its parent. This approach substantially improved the performance of classical wavelet denoising algorithms, both in terms of SNR and in terms of visual artifacts. A simulated MEMS microstructure signal is analyzed.

Info:

Periodical:

Key Engineering Materials (Volumes 381-382)

Edited by:

Wei Gao, Yasuhiro Takaya, Yongsheng Gao and Michael Krystek

Pages:

69-72

DOI:

10.4028/www.scientific.net/KEM.381-382.69

Citation:

K. Hu et al., "Signal Denoising of MEMS Microstructure Profile", Key Engineering Materials, Vols. 381-382, pp. 69-72, 2008

Online since:

June 2008

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Price:

$35.00

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