搜索结果: 1-15 共查到“统计学 Deconvolution”相关记录26条 . 查询时间(0.063 秒)
Noisy Laplace deconvolution with error in the operator
Laplace convolution blind deconvolution nonparametric adaptive estima-tion linear inverse problems error in the operator
2013/4/28
We adress the problem of Laplace deconvolution with random noise in a regression framework. The time set is not considered to be fixed, but grows with the number of observation points. Moreover, the c...
Revisiting Bayesian Blind Deconvolution
Blind deconvolution blind image deblurring variational Bayes sparse priors sparse estimation
2013/6/14
Blind deconvolution involves the estimation of a sharp signal or image given only a blurry observation. Because this problem is fundamentally ill-posed, strong priors on both the sharp image and blur ...
Multichannel Deconvolution with Long-Range Dependence: A Minimax Study
adaptivity Besov spaces block thresholding deconvolu-tion Fourier analysis functional data long-range dependence,Meyer wavelets mini-max estimators multichannel deconvolution partial differential equations stationary sequences wavelet analysis
2013/6/13
We consider the problem of estimating the unknown response function in the multichannel deconvolution model with long-range dependent Gaussian errors. We do not limit our consideration to a specific t...
Variational Semi-blind Sparse Deconvolution with Orthogonal Kernel Bases and its Application to MRFM
Variational Bayesian inference posterior image distribution image reconstruction hyperparameter estimation MRFM experiment
2013/5/2
We present a variational Bayesian method of joint image reconstruction and point spread function (PSF) estimation when the PSF of the imaging device is only partially known. To solve this semi-blind d...
Adaptive quantile estimation in deconvolution with unknown error distribution
Deconvolution Quantile and distribution function Adaptive es-timation Minimax convergence rates Random Fourier multiplier
2013/4/27
We study the problem of quantile estimation in deconvolution with ordinary smooth error distributions. In particular, we focus on the more realistic setup of unknown error distributions. We develop a ...
Wavelet Deconvolution in a Periodic Setting with Long-Range Dependent Errors
Besov Spaces Deconvolution fractional Brownian motion Long-Range Dependence Maxiset theory Wavelet Analysis
2012/9/17
In this paper, a hard thresholding wavelet estimator is constructed for a deconvolution model in a periodic setting that has long-range dependent noise. The estimation paradigm is based on a maxiset m...
A uniform central limit theorem and efficiency for deconvolution estimators
Deconvolution Donsker theorem Efficiency Distribution function Smoothed empirical processes Fourier multiplier
2012/9/17
We estimate linear functionals in the classical deconvolution problem by kernel esti-mators. We obtain a uniform central limit theorem with √n–rate on the assumption that the smoothness of the functio...
Laplace deconvolution and its application to Dynamic Contrast Enhanced imaging
Laplace deconvolution complexity penalty Dynamic Contrast Enhanced imaging
2012/9/19
In the present paper we consider the problem of Laplace deconvolution with noisy discrete observations. The study is motivated by Dynamic Contrast Enhanced imaging using a bolus of contrast agent, a p...
Laplace deconvolution with noisy observations
adaptivity kernel estimation minimax rates Volterra equation
2011/7/19
In the present paper we consider Laplace deconvolution on the basis of discrete noisy data observed on the interval which length may increase with a sample size. Although this problem arises in a vari...
Multiscale Methods for Shape Constraints in Deconvolution
Brownian motion convexity di erential inequalities ill-posed problems
2011/7/19
We derive multiscale statistics for deconvolution in order to detect qualitative features of the unknown density. An important example covered within this framework is to test for local monotonicity o...
Deconvolution of mixing time series on a graph
Deconvolution of mixing time latent time series state-space model
2011/6/17
In many applications we are interested in making
inference on latent time series from indirect
measurements, which are often low-dimensional
projections resulting from mixing or aggregation.
Posit...
A Bayesian Model of NMR Spectra for the Deconvolution and Quantification of Metabolites in Complex Biological Mixtures
metabolomics concentration estimation prior information multi component model block updates
2011/6/17
Nuclear Magnetic Resonance (NMR) spectra are widely used in metabolomics to
obtain profiles of metabolites dissolved in biofluids such as cell supernatants. Methods
for estimating metabolite concent...
Multichannel Boxcar Deconvolution with Growing Number of Channels
Adaptivity badly approximable tuples Besov spaces Diophantine approxi-mation functional deconvolution Fourier analysis Meyer wavelets nonparametric estimation wavelet analysis
2011/3/21
We consider the problem of estimating the unknown response function in the multichannel deconvolution model with a boxcar-like kernel which is of particular interest in signal processing. It is known ...
Kernel methods and minimum contrast estimators for empirical deconvolution
bandwidth inverse problems kernel estimators local linearmethods local polynomial methods minimum contrast methods
2010/3/11
We survey classical kernel methods for providing nonparametric solutions
to problems involving measurement error. In particular we outline
kernel-basedmethodology in this setting, and discuss its ba...
Deconvolution in High-Energy Astrophysics: Science, Instrumentation, and Methods
Background Contamination Censoring Chandra X-ray Observatory EM-type Algorithms Frequency Evaluations Markov chain Monte Carlo Measurement Errors
2009/9/21
In recent years, there has been an avalanche of new data in observa-
tional high-energy astrophysics. Recently launched or soon-to-be launched space-
based telescopes that are designed to detect and...