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Summary: Spatial-Temporal Modelling for Electrical Impedance
Imaging of a Mixing Process
Robert M West1
, Sha Meng2
, Robert G Aykroyd2
, and
Richard A Williams3
1
Biostatistics Unit, University of Leeds, 2
Department of
Statistics, University of Leeds, and 3
School of Process,
Environmental and Materials Engineering, University of Leeds
Abstract. The use of electrical tomography techniques for process visualisation and
investigation is a well-known example of a nonlinear, ill-posed and under-determined
inverse problem. Hence stable and reliable solution is not possible using measured data
alone, but requires regularization through prior information. The r^ole of a Bayesian
approach is therefore of fundamental importance, and when coupled with Markov chain
Monte Carlo (MCMC) sampling, it can provide valuable statistical information about
solution behaviour and reliability, rather than only a single image reconstruction with
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