A Bayesian approach to characterizing uncertainty in inverse problems using coarse and fine-scale information

IEEE Transactions on Signal Processing

Volumn 50, Issue 2, 2002, Pages 389-399

  Higdon, Dave ^a,b   Lee, Herbert ^b   Bi, Zhuoxin ^b  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

^b DUKE UNIVERSITY   (United States)

Author keywords

Coupled MCMC; Flow in porous media; Hydrology; Markov chain Monte Carlo; Posterior simulation; SPECT; Stochastic simulation

Indexed keywords

COMPUTATIONAL METHODS; COMPUTER SIMULATION; HYDROLOGY; INVERSE PROBLEMS; MARKOV PROCESSES; MONTE CARLO METHODS; POROUS MATERIALS; RANDOM PROCESSES; TOMOGRAPHY;

FINITE-SCALE INFORMATION; MARKOV CHAIN MONTE CARLO (MCMC) METHODS;

IMAGE RECONSTRUCTION;

EID: 0036475296     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.978393     Document Type: Article

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