Journal of Applied Sciences1812-56541812-5662Asian Network for Scientific Information10.3923/jas.2014.137.143LeiShaoDeyunChenMingGaoLiliWangYuChenXiaoyangYu22014142A novel image reconstruction algorithm which is based on Pulse
Coupled Neural Network (PCNN) is presented in this study. This algorithm is
used to solve “soft-field effect”
and ill-posed problems in Electrical Capacitance Tomography Technology (ECT).
Based on the analysis of the basic principle of electrical capacitance tomography
and PCNN, the calculation of PCNN and the calculation steps of automatically
setting the parameters are deduced for solving ECT inverse problem. Experiment
and simulation results indicate that the algorithm can provide high quality
images. It has the advantages of favorable stabilization and high speed of reconstructing
image. It is easier to implement compared with Linear Back Projection Algorithms
(LBP), Landweber algorithms and conjugate gradient algorithms (CG). This new
algorithm presents a feasible and effective way to research the image reconstruction
for electrical capacitance tomography system.]]>Loser, T., R. Wajman and D. Mewes,2001Liu, X., Y. Yu and C. Hu,2009Ghanbari, K.,2008Gosselin, L., M. Tye-Gingras and F. Mathieu-Potvin,2009Daoye, Y., Z. Bin and W. Shimin,2009Zhiyao, H., L. Xia, J. Haifeng, B. Wang and H. Li,2009Yang, W.,2010Li, Y. and W. Yang,2009Grudzien, K., A. Romanowski, Z. Chaniecki, M. Niedostatkiewicz and D. Sankowski,2010Ge, Z. and Z. Song,2010Cheng, D., X. Tang and J. Liu and X. Liu,2008Cheng, F.Y.,2009Ma, Y.D. and C.L. Qi,2006Chen, D., L. Wang, Z. Li, W. Shi, X. Yu and J. Zhang,2008Wang, L., Y. Chen, D. Chen and X. Yu,2010