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ICASSP
2011
IEEE
12 years 8 months ago
Maximum a posteriori based regularization parameter selection
The 1 norm regularized least square technique has been proposed as an efficient method to calculate sparse solutions. However, the choice of the regularization parameter is still...
Ashkan Panahi, Mats Viberg
TWC
2008
156views more  TWC 2008»
13 years 4 months ago
Low-Complexity Map Channel Estimation for Mobile MIMO-OFDM Systems
Abstract-- This paper presents a reduced-complexity maximum a posteriori probability (MAP) channel estimator with iterative data detection for orthogonal frequency division multipl...
Jie Gao, Huaping Liu
ICCV
1995
IEEE
13 years 8 months ago
Bayesian Decision Theory, the Maximum Local Mass Estimate, and Color Constancy
Computational vision algorithms are often developed in a Bayesian framework. Two estimators are commonly used: maximum a posteriori (MAP), and minimum mean squared error (MMSE). W...
William T. Freeman, David H. Brainard
PIMRC
2008
IEEE
13 years 10 months ago
Bayesian inference in linear models with a random Gaussian matrix : Algorithms and complexity
—We consider the Bayesian inference of a random Gaussian vector in a linear model with a random Gaussian matrix. We review two approaches to finding the MAP estimator for this m...
Ido Nevat, Gareth W. Peters, Jinhong Yuan