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Maximum a posteriori estimation approach to sparse recovery
2011 17th International Conference on Digital Signal Processing (DSP), 2011We adopt a maximum a posteriori (MAP) estimation based approach for recovering sparse signals from a small number of measurements formed by computing the inner products of the signal with rows of a matrix. We assume that each component of the sparse signal is independent and identically distributed (i.i.d) random variable drawn from a Gaussian mixture ...
Md Mashud Hyder, Kaushik Mahata
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Maximum-a-posteriori estimation with unknown regularisation parameters
2015 23rd European Signal Processing Conference (EUSIPCO), 2015This paper presents two hierarchical Bayesian methods for performing maximum-a-posteriori inference when the value of the regularisation parameter is unknown. The methods are useful for models with homogenous regularisers (i.e., prior sufficient statistics), including all norms, composite norms and compositions of norms with linear operators.
Marcelo Pereyra +2 more
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Maximum a posteriori estimation of room impulse responses
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015Estimating room impulse responses (RIRs) has a number of applications, including personalized audio, analyzing and improving acoustic behavior of concert halls, listening room compensation, sound source localization, and many others. RIRs have been estimated in essentially the same fashion for the last 50 years: Compute the cross correlation between a ...
Dinei A. F. Florêncio, Zhengyou Zhang
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Maximum A Posteriori Estimation of Height Profiles in InSAR Imaging
IEEE Geoscience and Remote Sensing Letters, 2004We present a statistical method to solve the height estimation problem in interferometric synthetic aperture radar (InSAR) applications. It is based on the use of multifrequency SAR raw datasets obtained by partitioning in subbands the available raw data spectrum, and on a Bayesian estimator using Markov random fields to model the a priori distribution
Giancarlo Ferraiuolo +2 more
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Maximum a Posteriori Estimation of Dynamically Changing Distributions
2009This paper presents a sequential state estimation method with arbitrary probabilistic models expressing the system's belief. Probabilistic models can be estimated by Maximum a posteriori estimators (MAP), which fail, if the state is dynamic or the model contains hidden variables.
Michael Volkhardt +3 more
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Maximum a Posteriori Parameter Estimation in Large Scale Systems
IFAC Proceedings Volumes, 1981Abstract In this paper we examine the use of the maximum a posteriori (MAP) approach for parameter estimation in large scale interconnected dynamical systems. We examine both the suboptimal approach of Sage and the optimal approaches which arise on solving within a multi-level structure the resulting non-linear two point boundary value problem.
Chemouil, Prosper +3 more
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Maximum a Posteriori Estimation of Multichannel Bernoulli-Gaussian Sequences
IEEE Transactions on Information Theory, 1989General problems and solutions are described for maximum a posteriori (MAP) estimation of multichannel Bernoulli-Gaussian sequences, which are the inputs to a linear discrete-time multivariable system. We first develop a separation principle, which indicates that one may estimate multichannel Gaussian amplitudes and Bernoulli events separately. We then
J M Mendel
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Maximum A Posteriori Estimation of Time Delay
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2007Time-delay estimation (TDE) is an important topic of array signal processing for applications such as source localization and beam-forming. With a pair of sensors, the generalized cross correlation (GCC) method is widely used for TDE and the maximum-likelihood (ML) estimation can be considered as a GCC prefilter.
Bowon Lee, Ton Kalker
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Spatiotemporal wavelet maximum a posteriori estimation for video denoising
Journal of Electronic Imaging, 2010We examine one way to extend recently proposed wavelet-based maximum a posteriori estimation rules for image denoising to video. The proposed approach takes into account both spatial and temporal dependencies between wavelet coefficients, and is general enough to incorporate different spherically contoured prior distributions on noiseless coefficients,
Pavel A. Khazron, Ivan W. Selesnick
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Maximum Likelihood and Maximum a Posteriori Direction-of-Arrival Estimation in the Presence of Sirp Noise [PDF]
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016 The maximum likelihood (ML) and maximum a posteriori (MAP) estimation techniques are widely used to address the direction-of-arrival (DOA) estimation problems, an important topic in sensor array processing. Conventionally the ML estimators in the DOA estimation context assume the sensor noise to follow a Gaussian distribution. In real-life application,
Mohammed Nabil El Korso +1 more
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