Multiscale maximum penalized likelihood estimators

被引：1
|
作者：
Nowak, RD [1 ]
Kolaczyk, ED [1 ]
机构：
[1] Rice Univ, Houston, TX 77251 USA
来源：
ISIT: 2002 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY, PROCEEDINGS | 2002年
关键词：
D O I：
10.1109/ISIT.2002.1023428
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We present a new class of maximum penalized likelihood estimators which are analogues of popular wavelet denoising methods. The new estimators move beyond the standard signal plus Gaussian noise model to handle a much broader class of nonparametric function estimation problems including Poisson and multinomial data types. The estimators share the same sort of adaptivity and near-optimality properties as wavelet denoising methods.
引用
收藏
页码：156 / 156
页数：1
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