Results 201 to 210 of about 136,829,320 (227)

Maximum a posteriori estimation of relative abundances of protein conformations

2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015
Estimation of mixture coefficients of protein conformations find applications in understanding protein behavior. We describe a method for maximum a posteriori (MAP) estimation of the mixture coefficients of ensemble of conformations in a protein mixture solution using measured small angle X-ray scattering (SAXS) intensities.
A. Emre Onuk, Murat Akçakaya, Jaydeep P. Bardhan, Deniz Erdogmus, Dana H. Brooks, Lee Makowski   +5 more
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Solving the equation for the maximum a posteriori estimate

Proceedings of the IEEE, 1969
An iterative technique is given for solving the equation for the maximum a posteriori estimate of the modulation on a carrier which is combined with noise. The method has been tested in the FM case with satisfactory results.
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Maximum a posteriori estimation for radar angular super-resolution

2014 IEEE Geoscience and Remote Sensing Symposium, 2014
Angular super-resolution performance is the key problem in the field of radar imaging. In this paper, we propose an approach to radar angular super-resolution through deconvolution, which is able to increase the resolution of radar image beyond the limitation of system parameters.
Yuebo Zha, Yulin Huang 0001, Jianyu Yang 0001, Junjie Wu 0001, Yin Zhang 0003   +4 more
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Maximum-a-posteriori estimation of jump Box-Jenkins models

2019 IEEE 58th Conference on Decision and Control (CDC), 2019
Complex dynamical systems and time series can often be described by jump models, namely finite collections of local models where each sub-model is associated to a different operating condition of the system or segment of the time series. Learning jump models from data thus requires both the identification of the local models and the reconstruction of ...
Valentina Breschi, Dario Piga, Alberto Bemporad   +2 more
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A Minorization-Maximization Algorithm for Maximum a Posteriori Signal Estimation

2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
We develop an iterative algorithm based on minorization - maximization optimization to determine the maximum a posteriori estimate of the signal. We focus on linear Gaussian signal model with a family of heavy-tailed prior distributions which can be represented as scale mixture of Gaussian. We then modify the proposed algorithm for wavelet domain image
Guang Deng, Wai-Yin Ng
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Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier

2011
In this paper we propose a new classification criterion based on maximum a posteriori (MAP) estimation for a binary problem. In our method, we do not estimate the posteriori probability; instead we construct a discriminant function that provides the same result.
Tatsuya Yokota, Yukihiko Yamashita
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Maximum A Posteriori Estimation of Energetics in Silicon Self-diffusion

Proceedings of the 44th IEEE Conference on Decision and Control, 2006
Maximum A Posteriori (MAP) estimation was employed to refine estimates of various energetics in silicon self-diffusion. Self-diffusion profiles were augmented with prior parameter estimates determined from previous experimental systems to obtain improved values. Parameter sensitivity analysis was utilized before MAP estimation to determine the relative
Charlotte T. M. Kwok, Kapil Dev, Edmund G. Seebauer, Richard D. Braatz   +3 more
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Registration of Noisy Images via Maximum A-Posteriori Estimation

2014
Biomedical image registration faces challenging problems induced by the image acquisition process of the involved modality. A common problem is the omnipresence of noise perturbations. A low signal-to-noise ratio – like in modern dynamic imaging with short acquisition times – may lead to failure or artifacts in standard image registration techniques. A
Sebastian Suhr, Daniel Tenbrinck, Martin Burger 0001, Jan Modersitzki   +3 more
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A Variational Approach to Maximum a Posteriori Estimation for Image Denoising

2001
Using first principles, we establish in this paper a connection between the maximum a posteriori (MAP) estimator and the variational formulation of optimizing a given functional subject to some noise constraints. A MAP estimator which uses a Markov or a maximum entropy random field model for a prior distribution can be viewed as a minimizer of a ...
A. Ben Hamza, Hamid Krim
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Estimating the Number of Communities Based on Maximum a Posteriori

International Journal of Pattern Recognition and Artificial Intelligence
Community structure is one of the important characteristics of complex networks. Community discovery or detection has important theoretical significance and practical value. At present, estimation of the number of communities (or clusters) is still an open question. By Bayesian inference, this research deduces the relationship between maximum possible
Ningsi Li, Chuanpeng Wang, Dong Li
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