An efficient approach for limited-data chemical species tomography and its error bounds

N. Polydorides, S. A. Tsekenis, H. McCann, V. -D. A. Prat, P. Wright

Research output: Contribution to journalArticlepeer-review

Abstract

We present a computationally efficient reconstruction method for the limited-data chemical species tomography problem that incorporates projection of the unknown gas concentration function onto a low-dimensional subspace, and regularization using prior information obtained from a simple flow model. In this context, the contribution of this work is on the analysis of the projection-induced data errors and the calculation of bounds for the overall image error incorporating the impact of projection and regularization errors as well as measurement noise. As an extension to this methodology, we present a variant algorithm that preserves the positivity of the concentration image.
Original languageEnglish
Article number20150875
Number of pages17
JournalProceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume472
Issue number2187
Early online date1 Mar 2016
DOIs
Publication statusPublished - 31 Mar 2016

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