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% This collection of codes accompanies the SIAM Book: % % "Computational Uncertainty Quantification for Inverse Problems" % % by Johnathan M. Bardsley % % The codes come with no guarantees of any kind. % % The figures in the book were generated using these codes, % though when the codes are run, most results will be slightly % different than those in the book, due to different random vector % realizations. % % The driver codes for specific chapters are found within the % respective directories: Chapter 1, Chapter 2, etc. To run a % driver code, open MATLAB and change directories to the % chapter directory of interest, type the name of the file that % you want to run on the command line and hit return. % % For example, in the Chapter 1 directory, you could type % % >> Deblur1d % % and then hit enter. This will generate several of the figures % corresponding to the deblurring example in Chapter 1. % % The MatFiles directory contains the true images used in the % two-dimensional test cases: satellite.mat, cell.mat, and % SheppLogan.mat % % The Functions directory contains additional functions needed to % run the driver codes, e.g., preconditioned conjugate gradient % (CG.m), adaptive Metropolis (AM.m), and the Geweke test (geweke.m), % to name a few.
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MATLAB codes for "Computational Uncertainty Quantification for Inverse Problems," by Johnathan M. Bardsley
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