Titlebook: Wavelets and Statistics; Anestis Antoniadis,Georges Oppenheim Book 1995 Springer-Verlag New York 1995 Gaussian process.Hypothese.Markov ra

管玄樂團(tuán)

書目名稱Wavelets and Statistics影響因子(影響力)




書目名稱Wavelets and Statistics影響因子(影響力)學(xué)科排名




書目名稱Wavelets and Statistics網(wǎng)絡(luò)公開度




書目名稱Wavelets and Statistics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Wavelets and Statistics被引頻次




書目名稱Wavelets and Statistics被引頻次學(xué)科排名




書目名稱Wavelets and Statistics年度引用




書目名稱Wavelets and Statistics年度引用學(xué)科排名




書目名稱Wavelets and Statistics讀者反饋




書目名稱Wavelets and Statistics讀者反饋學(xué)科排名

forager

instructive

Thresholding of Wavelet Coefficients as Multiple Hypotheses Testing Procedure,t coefficients among those chosen for the wavelet reconstruction. The resulting procedure is inherently adaptive, and responds to the complexity of the estimated function. Finally, comparing the proposed FDR-threshold with that fixed global of Donoho and Johnstone by evaluating the relative Mean-Squ

Mumble

Thresholding of Wavelet Coefficients as Multiple Hypotheses Testing Procedure,t coefficients among those chosen for the wavelet reconstruction. The resulting procedure is inherently adaptive, and responds to the complexity of the estimated function. Finally, comparing the proposed FDR-threshold with that fixed global of Donoho and Johnstone by evaluating the relative Mean-Squ

玷污

Translation-Invariant De-Noising,-noising using the undecimated or stationary wavelet transform..Cycle-spinning exhibits benefits outside of wavelet de-noising, for example in cosine packet denoising, where it helps suppress ‘clicks’. It also has a counterpart in frequency domain de-noising, where the goal of translation-invariance

Itinerant

Translation-Invariant De-Noising,-noising using the undecimated or stationary wavelet transform..Cycle-spinning exhibits benefits outside of wavelet de-noising, for example in cosine packet denoising, where it helps suppress ‘clicks’. It also has a counterpart in frequency domain de-noising, where the goal of translation-invariance

Projection

Wavelet Thresholding: Beyond the Gaussian I.I.D. Situation,matically adapts to possibly different degrees of regularity for the different directions. The resulting fully-adaptive spectral estimator attains the rate that is optimal in the idealized Gaussian white noise model up to a logarithmic factor.

thwart

Wavelet Thresholding: Beyond the Gaussian I.I.D. Situation,matically adapts to possibly different degrees of regularity for the different directions. The resulting fully-adaptive spectral estimator attains the rate that is optimal in the idealized Gaussian white noise model up to a logarithmic factor.

把…比做

Book 1995his volume reflects the broad spectrum of the conference. as it includes 21 articles contributed by specialists in various areas in this field. The material compiled is fairly wide in scope and ranges from the development of new tools for non parametric curve estimation to applied problems, such as

demote