Wavelet Deconvolution in a Periodic Setting Using Cross-Validation

Leming Qu; Partha S. Routh; Kyungduk Ko

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

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	American English
Journal	IEEE Signal Processing Letters
State	Published - 1 Apr 2006

Keywords

Cross-validation (CV)
wavelet deconvolution

EGS Disciplines

Applied Mathematics
Mathematics

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Wavelet Deconvolution in a Periodic Setting Using Cross-ValidatioFinal published version, 182 KBLicense: Unspecified

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{\textquoteright}s performance is compared with the fixed constant tuning and the default tuning in WaveD.",

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author = "Leming Qu and Routh, {Partha S.} and Kyungduk Ko",

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TY - JOUR

T1 - Wavelet Deconvolution in a Periodic Setting Using Cross-Validation

AU - Qu, Leming

AU - Routh, Partha S.

AU - Ko, Kyungduk

PY - 2006/4/1

Y1 - 2006/4/1

N2 - 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.

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.

KW - Cross-validation (CV)

KW - wavelet deconvolution

UR - https://scholarworks.boisestate.edu/math_facpubs/1

M3 - Article

SN - 1070-9908

JO - IEEE Signal Processing Letters

JF - IEEE Signal Processing Letters

ER -

Wavelet Deconvolution in a Periodic Setting Using Cross-Validation

Abstract

Keywords

EGS Disciplines

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