@Article{JFBI-8-125,
author = {Qifang Liu, Han Yan and Xixiang Zhang},
title = {Fast Image Reconstruction Research Based on H∞ Filtering for Electrical Resistance Tomography},
journal = {Journal of Fiber Bioengineering and Informatics},
year = {2015},
volume = {8},
number = {1},
pages = {125--132},
abstract = {In order to improve the image reconstructed quality affected by soft filed feature and the speed of dynamic
on-line data processing in Electrical Resistance Tomography, we propose a fast image reconstruction
algorithm based on H∞ filtering theory. Mainly, on the H∞ filtering principle, a dynamic system is
formulated firstly, whose inputs have unknown disturbances including noise errors and model errors, and
the outputs have the estimation errors. Then, making the H∞ norm of this dynamic system as a cost
function, a fast H∞ filtering algorithm is proposed whose criterion is to guarantee that the worst-cast
effect of disturbance on estimation error is smaller than a given boundary. Experimental work was carried
out for three typical flow distributions. Results showed that H∞ filter method improves the resolution of
the reconstructed images and gains the strong robustness and anti-interference performance in unknown
interference noise conditions. In addition, it dramatically reduces the computational time compared with
the traditional Gauss-Newton iterative and Kalman filter methods. Therefore, the method is suitable
for on-line multiphase flow measurement.},
issn = {2617-8699},
doi = {https://doi.org/10.3993/jfbi03201512},
url = {http://global-sci.org/intro/article_detail/jfbi/4692.html}
}