首页> 外文期刊>The Annals of Statistics: An Official Journal of the Institute of Mathematical Statistics >Wavelet thresholding for nonnecessarily Gaussian noise: Functionality
【24h】

Wavelet thresholding for nonnecessarily Gaussian noise: Functionality

机译:高斯噪声不必要的小波阈值:功能

获取原文
获取原文并翻译 | 示例
           

摘要

For signals belonging to balls in smoothness classes and noise with enough moments, the asymptotic behavior of the minimax quadratic risk among soft-threshold estimates is investigated. In turn, these results, combined with a median filtering method, lead to asymptotics for denoising heavy tails via wavelet thresholding. Some further comparisons of wavelet thresholding and of kernel estimators are also briefly discussed.
机译:对于属于光滑度类别的球的信号以及具有足够矩的噪声,研究了软阈值估计中的最小极大二次风险的渐近行为。反过来,这些结果与中值滤波方法相结合,导致通过小波阈值对重尾进行消噪的渐近性。还简要讨论了小波阈值和核估计器的一些其他比较。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号