Adapting to Unknown Smoothness via Wavelet Shrinkage Export

@article{donoho95, abstract = {We attempt to recover a function of unknown smoothness from noisy, sampled data. We introduce a procedure, SureShrink, which suppresses noise by thresholding the empirical wavelet coefficients. The thresholding is adaptive: a threshold level is assigned to each dyadic resolution level by the principle of minimizing the Stein Unbiased Estimate of Risk (Sure) for threshold estimates. The computational effort of the overall procedure is order N Δ log(N) as a function of the sample size N ....}, author = {Donoho, David L. and Johnstone, Iain M.}, citeulike-article-id = {1639705}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.5188}, journal = {Journal of the American Statistical Association}, keywords = {shrinkage, wavelet}, month = {December}, number = {432}, pages = {1200--1224}, posted-at = {2007-09-09 23:01:33}, priority = {2}, title = {Adapting to Unknown Smoothness via Wavelet Shrinkage}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.5188}, volume = {90}, year = {1995} }

TY - JOUR ID - donoho95 L3 - citeulike-article-id:1639705 N2 - We attempt to recover a function of unknown smoothness from noisy, sampled data. We introduce a procedure, SureShrink, which suppresses noise by thresholding the empirical wavelet coefficients. The thresholding is adaptive: a threshold level is assigned to each dyadic resolution level by the principle of minimizing the Stein Unbiased Estimate of Risk (Sure) for threshold estimates. The computational effort of the overall procedure is order N Δ log(N) as a function of the sample size N .... IS - 432 JF - Journal of the American Statistical Association EP - 1224 TI - Adapting to Unknown Smoothness via Wavelet Shrinkage VL - 90 SP - 1200 KW - shrinkage KW - wavelet AU - Donoho, David AU - Johnstone, Iain PY - 1995/12// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.33.5188 ER -