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Large scale inverse problems : computational methods and applications in the earth sciences /

This book is thesecond volume of three volume series recording the ""Radon Special Semester 2011 on Multiscale Simulation & Analysis in Energy and the Environment"" taking place in Linz, Austria, October 3-7, 2011. The volume addresses the common ground in the mathematical an...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Cullen, Michael J. P. (Editor ), Freitag, Melina A., 1980- (Editor ), Kindermann, Stefan, 1972- (Editor ), Scheichl, Robert, 1972- (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin ; Boston : De Gruyter, [2013]
Colección:Radon series on computational and applied mathematics.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Large scale inverse problems :  |b computational methods and applications in the earth sciences /  |c edited by Mike Cullen, Melina A. Freitag, Stefan Kindermann, Robert Scheichl. 
264 1 |a Berlin ;  |a Boston :  |b De Gruyter,  |c [2013] 
264 4 |c ©2013 
300 |a 1 online resource (ix, 203 pages) :  |b illustrations 
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490 1 |a Radon Series on Computational and Applied Mathematics 
504 |a Includes bibliographical references. 
505 0 |a Preface; Synergy of inverse problems and data assimilation techniques; 1 Introduction; 2 Regularization theory; 3 Cycling, Tikhonov regularization and 3DVar; 4 Error analysis; 5 Bayesian approach to inverse problems; 6 4DVar; 7 Kalman filter and Kalman smoother; 8 Ensemble methods; 9 Numerical examples; 9.1 Data assimilation for an advection-diffusion system; 9.2 Data assimilation for the Lorenz-95 system; 10 Concluding remarks; Variational data assimilation for very large environmental problems; 1 Introduction; 2 Theory of variational data assimilation. 
505 8 |a 2.1 Incremental variational data assimilation3 Practical implementation; 3.1 Model development; 3.2 Background error covariances; 3.3 Observation errors; 3.4 Optimization methods; 3.5 Reduced order approaches; 3.6 Issues for nested models; 3.7 Weak-constraint variational assimilation; 4 Summary and future perspectives; Ensemble filter techniques for intermittent data assimilation; 1 Bayesian statistics; 1.1 Preliminaries; 1.2 Bayesian inference; 1.3 Coupling of random variables; 1.4 Monte Carlo methods; 2 Stochastic processes; 2.1 Discrete time Markov processes. 
505 8 |a 2.2 Stochastic difference and differential equations2.3 Ensemble prediction and sampling methods; 3 Data assimilation and filtering; 3.1 Preliminaries; 3.2 SequentialMonte Carlo method; 3.3 Ensemble Kalman filter (EnKF); 3.4 Ensemble transform Kalman-Bucy filter; 3.5 Guided sequential Monte Carlo methods; 3.6 Continuous ensemble transform filter formulations; 4 Concluding remarks; Inverse problems in imaging; 1 Mathematicalmodels for images; 2 Examples of imaging devices; 2.1 Optical imaging; 2.2 Transmission tomography; 2.3 Emission tomography; 2.4 MR imaging; 2.5 Acoustic imaging. 
505 8 |a 2.6 Electromagnetic imaging3 Basic image reconstruction; 3.1 Deblurring and point spread functions; 3.2 Noise; 3.3 Reconstruction methods; 4 Missing data and prior information; 4.1 Prior information; 4.2 Undersampling and superresolution; 4.3 Inpainting; 4.4 Surface imaging; 5 Calibration problems; 5.1 Blind deconvolution; 5.2 Nonlinear MR imaging; 5.3 Attenuation correction in SPECT; 5.4 Blind spectral unmixing; 6 Model-based dynamic imaging; 6.1 Kinetic models; 6.2 Parameter identification; 6.3 Basis pursuit; 6.4 Motion and deformation models; 6.5 Advanced PDE models. 
505 8 |a The lost honor of l2-based regularization1 Introduction; 2 l1-based regularization; 3 Poor data; 4 Large, highly ill-conditioned problems; 4.1 Inverse potential problem; 4.2 The effect of ill-conditioning on L1 regularization; 4.3 Nonlinear, highly ill-posed examples; 5 Summary; List of contributors. 
520 |a This book is thesecond volume of three volume series recording the ""Radon Special Semester 2011 on Multiscale Simulation & Analysis in Energy and the Environment"" taking place in Linz, Austria, October 3-7, 2011. The volume addresses the common ground in the mathematical and computational procedures required for large-scale inverse problems and data assimilation in forefront applications. 
588 0 |a Print version record. 
542 1 |f This work is licensed under a Creative Commons license  |u https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode 
546 |a English. 
506 0 |a Open Access  |5 EbpS 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
590 |a De Gruyter Online  |b De Gruyter Open Access eBooks 
650 0 |a Inverse problems (Differential equations) 
650 6 |a Problèmes inverses (Équations différentielles) 
650 7 |a Applied mathematics.  |2 bicssc 
650 7 |a MATHEMATICS  |x Calculus.  |2 bisacsh 
650 7 |a MATHEMATICS  |x Mathematical Analysis.  |2 bisacsh 
650 7 |a Inverse problems (Differential equations)  |2 fast 
653 |a Data Assimilation. 
653 |a Geosciences. 
653 |a Ill-Posed Inverse Problems. 
653 |a Optimization. 
653 |a Regularization. 
700 1 |a Cullen, Michael J. P.,  |e editor. 
700 1 |a Freitag, Melina A.,  |d 1980-  |e editor.  |1 https://id.oclc.org/worldcat/entity/E39PBJbRjWgYw8MpXDwWhh9FKd 
700 1 |a Kindermann, Stefan,  |d 1972-  |e editor.  |1 https://id.oclc.org/worldcat/entity/E39PBJpDRPfyq9b4mtfmfkdCwC 
700 1 |a Scheichl, Robert,  |d 1972-  |e editor.  |1 https://id.oclc.org/worldcat/entity/E39PCjwRR9mJDtdQ6bYM3WxGQC 
758 |i has work:  |a Large scale inverse problems (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCGFRx4KBfKXYbdyjMMyBGd  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Scheichl, Robert.  |t Large Scale Inverse Problems : Computational Methods and Applications in the Earth Sciences.  |d Berlin : De Gruyter, ©2013  |z 9783110282221 
830 0 |a Radon series on computational and applied mathematics. 
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