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- W1992676433 abstract "In this paper we consider the reconstruction of rapidly varying objects in process tomography. The evolution of the physical parameters can often be approximated with stochastic convection-diffusion and fluid dynamics models. We use the state estimation approach to obtain the tomographic reconstructions and show how these flow models can be exploited with the actual observation models that by themselves induce ill-posed problems. The state estimation problem can be stated in different ways based on the available temporal information. We concentrate on such cases in which continuous monitoring is essential but a small delay for the reconstructions is allowable. The state estimation problem is solved with the fixed-lag Kalman smoother algorithm. As the boundary observations we use the voltage data of electrical impedance tomography. We also give a numerical illustration of the approach in a case in which we track a bolus that moves rapidly through a pipeline." @default.
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- W1992676433 date "2001-05-01" @default.
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- W1992676433 title "State estimation with fluid dynamical evolution models in process tomography - an application to impedance tomography" @default.
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- W1992676433 doi "https://doi.org/10.1088/0266-5611/17/3/307" @default.
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