DocumentCode
2054606
Title
Multiscale maximum penalized likelihood estimators
Author
Nowak, Robert D. ; Kolaczyk, Eric D.
Author_Institution
Rice Univ., Houston, TX, USA
fYear
2002
fDate
2002
Firstpage
156
Abstract
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.
Keywords
Gaussian noise; adaptive estimation; maximum likelihood estimation; signal processing; stochastic processes; wavelet transforms; Gaussian noise model; Poisson data; adaptive estimators; multinomial data; multiscale maximum penalized likelihood estimators; near-optimality properties; nonparametric function estimation; signal model; wavelet denoising methods; Data analysis; Information analysis; Instruments; Military computing; Noise reduction; Sampling methods; Statistical analysis; Stochastic processes; Upper bound; Wavelet analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on
Print_ISBN
0-7803-7501-7
Type
conf
DOI
10.1109/ISIT.2002.1023428
Filename
1023428
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