Bayesian wavelet denoising: Besov priors and non-Gaussian noises.

DOI10.1016/S0165-1684(00)00190-0zbMath1098.94560OpenAlexW2076141307MaRDI QIDQ5940756

Jean-Christophe Pesquet, D. Leporini

Publication date: 20 August 2001

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0165-1684(00)00190-0

zbMATH Keywords

Besov spaceMCMC methodNon-Gaussian noiseNonlinear estimationWavelet

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (6)

Wavelet shrinkage in nonparametric regression models with positive noise ⋮ Besov-Laplace priors in density estimation: optimal posterior contraction rates and adaptation ⋮ WAVELET-CONSTRAINED IMAGE RESTORATION ⋮ Sparsity-promoting and edge-preserving maximum a posteriori estimators in non-parametric Bayesian inverse problems ⋮ Wavelet thresholding for some classes of non–Gaussian noise ⋮ Nonparametric Bayesian inference for reversible multidimensional diffusions

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