Wavelet deconvolution in a periodic setting using cross-validation

Leming Qu; Partha S. Routh; Kyungduk Ko

doi:10.1109/LSP.2005.863657

Wavelet deconvolution in a periodic setting using cross-validation

Leming Qu, Partha S. Routh, Kyungduk Ko

Mathematics Department

Boise State University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

The wavelet deconvolution method WaveD using band-limited wavelets offers both theoretical and computational advantages over traditional compactly supported wavelets. The translation-invariant WaveD with a fast algorithm improves further. The twofold cross-validation method for choosing the threshold parameter and the finest resolution level in WaveD is introduced. The algorithm's performance is compared with the fixed constant tuning and the default tuning in WaveD.

Original language	English
Pages (from-to)	232-235
Number of pages	4
Journal	IEEE Signal Processing Letters
Volume	13
Issue number	4
DOIs	https://doi.org/10.1109/LSP.2005.863657
State	Published - Apr 2006

Keywords

Cross-validation (CV)
Wavelet deconvolution

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10.1109/LSP.2005.863657

Cite this

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title = "Wavelet deconvolution in a periodic setting using cross-validation",

abstract = "The wavelet deconvolution method WaveD using band-limited wavelets offers both theoretical and computational advantages over traditional compactly supported wavelets. The translation-invariant WaveD with a fast algorithm improves further. The twofold cross-validation method for choosing the threshold parameter and the finest resolution level in WaveD is introduced. The algorithm's performance is compared with the fixed constant tuning and the default tuning in WaveD.",

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AB - The wavelet deconvolution method WaveD using band-limited wavelets offers both theoretical and computational advantages over traditional compactly supported wavelets. The translation-invariant WaveD with a fast algorithm improves further. The twofold cross-validation method for choosing the threshold parameter and the finest resolution level in WaveD is introduced. The algorithm's performance is compared with the fixed constant tuning and the default tuning in WaveD.

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KW - Wavelet deconvolution

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Wavelet deconvolution in a periodic setting using cross-validation

Abstract

Keywords

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