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Inverse Imaging with Poisson Data

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Inverse Imaging with Poisson Data: From cells to galaxies

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Nonlinear Inverse Problems in Imaging

This book provides researchers and engineers in the imaging field with the skills they need to effectively deal with nonlinear inverse;

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Inverse Problems And Applications

in the Earth's interior, creation of astrophysical images from telescope data, finding cracks and interfaces within materials, shape optimization;

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Computational Methods for Applied Inverse Problems

of applications. This monograph reports recent advances of inversion theory and recent developments with practical applications in frontiers;

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Computational Methods for Inverse Problems in Imaging

This book presents recent mathematical methods in the area of inverse problems in imaging with a particular focus on the computational;

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Computational Methods for Inverse Problems in Imaging

This book presents recent mathematical methods in the area of inverse problems in imaging with a particular focus on the computational;

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Statistical Computing in Nuclear Imaging

data and Poisson approximations, are discussed in the first chapters. Monte Carlo methods and Markov chains in posterior analysis are discussed;

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Statistical Computing in Nuclear Imaging

data and Poisson approximations, are discussed in the first chapters. Monte Carlo methods and Markov chains in posterior analysis are discussed;

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Nonlinear inverse finite element methods in electrical tomography

forward and inverse porblems are given. Experimental data from electrical impedance tomography, electrical capacitance tomography and;

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Optimization in Computational Imaging and Inverse Problems

result that one can get with that data and will it be acceptable? We use optimization theory to analyze inverse problems such as this and;

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Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms

resolution, pulse compression and image formation are given together with associated MATLAB codes. After providing the fundamentals for ISAR imaging;

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Time-dependent Problems in Imaging and Parameter Identification

Inverse problems such as imaging or parameter identification deal with the recovery of unknown quantities from indirect observations;

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Seismic Imaging and Inversion

Extracting information from seismic data requires knowledge of seismic wave propagation and reflection. The commonly used method involves;

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Seismic Imaging And Inversion: Volume 1

Extracting information from seismic data requires knowledge of seismic wave propagation and reflection. The commonly used method involves;

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Inverse Synthetic Aperture Radar Imaging With MATL AB Algorithms, Second Edition

Build your knowledge of SAR/ISAR imaging with this comprehensive and insightful resource The newly revised Second Edition of Inverse;

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Residual Stress, Thermomechanics & Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 9

Residual Stress, Thermomechanics& Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 9;...

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Introduction to Imaging from Scattered Fields

measurements. The PDFT restores stability and improves estimates of the object even with severely limited data (provided it is sufficient to meet a;

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Software Reliability Growth Models

discusses SRGM based on the non-homogeneous Poisson process (NHPP), which has been a quite successful tool in practical software reliability;

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Software Reliability Growth Models

discusses SRGM based on the non-homogeneous Poisson process (NHPP), which has been a quite successful tool in practical software reliability;

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Introduction to Imaging from Scattered Fields

stability and improves estimates of the object even with severely limited data (provided it is sufficient to meet a criterion based on the number;

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Inverse Synthetic Aperture Radar Imaging

target recognition, this book provides readers with knowledge of various algorithms of ISAR imaging of targets and implementation with MATLAB. It;

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Data Assimilation

Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places;

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Integrated Imaging Of The Earth Coupled

of how to best integrate different geophysical datasets with geological prior understanding and other complimentary data. This foundational basis;

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Bayesian Approach to Inverse Problems

recover a quantity of interest from measurable data. Unfortunately, most inverse problems are ill-posed, which means that precise and stable;

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Residual Stress Thermomechanics Infrared Imaging Hybrid Techniques and Inver

Residual Stress, Thermomechanics& Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 9;...

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An Introduction to Data Analysis and Uncertainty Quantification for Inverse Problems

data, and limitations in the number of observations; thus it is important to include an assessment of the uncertainties as part of the solution;

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