A trimmed translation-invariant denoising estimator

References

• Jin , J. and Shi , J. 2001 . Automatic feature extraction of waveform signals for in-process diagnostic performance improvement . J. Intell. Manuf. , 12 : 257 – 268 .
   Web of Science ®Google Scholar
• Walker , E. and Wright , S. P. 2002 . Comparing curves using additive models . J. Qual. Technol. , 34 : 118 – 129 .
   Web of Science ®Google Scholar
• Ogden , R. 1997 . Essential Wavelets for Statistical Applications and Data Analysis , Boston : Birkhäuser .
   Google Scholar
• Vidakovic , B. 1999 . Statistical Modeling by Wavelets , New York : John Wiley and Sons .
   Google Scholar
• Nason , G. P. 2008 . “ Wavelet Methods in Statistics with R ” . New York : Springer .
   Google Scholar
• Coifman , R. and Donoho , D. 1995 . “ Translation-invariant wavelet denoising ” . In Wavelets and Statistics , Edited by: Antoniadis , A. and Oppenheim , G. 125 – 150 . New York : Springer-Verlag .
   Google Scholar
• Nason , G. and Silverman , B. 1995 . “ The stationary wavelet transform and some statistical applications ” . In Wavelets and Statistics , Edited by: Antoniadis , A. and Oppenheim , G. 281 – 300 . New York : Springer-Verlag .
   Google Scholar
• Mallat , S. 1999 . A Wavelet Tour of Signal Processing , 2 , San Diego , CA : Academic Press .
   Google Scholar
• Donoho , D. and Johnstone , I. 1994 . Ideal spatial adaptation via wavelet shrinkage . Biometrika , 81 : 425 – 455 .
   Web of Science ®Google Scholar
• Daubechies , I. 1992 . Ten Lectures on Wavelets , Philadelphia : SIAM .
   Google Scholar
• Abramovich , F. and Benjamini , Y. 1996 . Adaptive thresholding of wavelet coefficients . Comput. Stat. Data Anal. , 22 : 351 – 361 .
   Web of Science ®Google Scholar
• Abramovich , F. , Sapatinas , T. and Silverman , B. W. 1998 . Wavelet thresholding via a Bayesian approach . J. R. Stat. Soc. Ser. B Stat. Methodol. , 60 : 725 – 749 .
   Web of Science ®Google Scholar
• Antoniadis , A. 1997 . Wavelets in statistics: A review . Stat. Methods Appl. , 6 : 97 – 130 .
   Google Scholar
• Azzalini , A. , Farge , M. and Schneider , K. 2005 . Nonlinear wavelet thresholding: A recursive method to determine the optimal denoising threshold . Appl. Comput. Harmon. Anal. , 18 : 177 – 185 .
   Web of Science ®Google Scholar
• Cai , T. 1999 . Adaptive wavelet estimation: A block thresholding and oracle inequality approach . Ann. Stat. , 27 : 898 – 924 .
   Web of Science ®Google Scholar
• Cai , T. and Silverman , B. 2001 . Incorporating information on neighboring coefficients into wavelet estimation . Sankhya Ser. , B 63 : 127 – 148 .
   Google Scholar
• Chicken , E. 2003 . Block thresholding and wavelet estimation for nonequispaced samples . J. Stat. Plan. Inference , 116 : 113 – 129 .
   Web of Science ®Google Scholar
• Chicken , E. 2005 . Block-dependent thresholding in wavelet regression . J. Nonparametr. Stat. , 17 : 467 – 491 .
   Web of Science ®Google Scholar
• Chipman , H. A. and Kolaczyk , E. D. 1997 . Adaptive Bayesian wavelet shrinkage . J. Am. Stat. Assoc. , 92 : 1413 – 1421 .
   Web of Science ®Google Scholar
• Donoho , D. and Johnstone , I. 1998 . Minimax estimation via wavelet shrinkage . Ann. Stat. , 26 : 879 – 921 .
   Web of Science ®Google Scholar
• Jansen , M. 2001 . Noise Reduction by Wavelet Thresholding , New York : Springer .
   Google Scholar
• Jansen , B. A. and Malfait , M. 1997 . Generalized cross validation for wavelet thresholding . Signal Process. , 56 : 33 – 44 .
   Web of Science ®Google Scholar
• Nason , G. P. 1996 . Wavelet shrinkage using cross-validation . J. R. Stat. Soc. Ser. B Stat. Methodol. , 58 : 463 – 479 .
   Web of Science ®Google Scholar
• Vidakovic , B. 1998 . Nonlinear wavelet shrinkage with Bayes rules and Bayes factors . J. Am. Stat. Assoc. , 93 : 173 – 179 .
   Web of Science ®Google Scholar
• R Development Core Team . 2009 . R: A Language and Environment for Statistical Computing , Vienna , , Austria : R Foundation for Statistical Computing . ISBN 3-900051-07-0. Available at http://www.R-project.org
   Google Scholar
• Whitcher , B. Waveslim: Basic wavelet routines for one-, two- and three-dimensional signal processing R package version 1.6.3, 2009. Available at http://CRAN.R-project.org/package=waveslim
   Google Scholar