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Journal of Applied Sciences
  Year: 2014 | Volume: 14 | Issue: 2 | Page No.: 137-143
DOI: 10.3923/jas.2014.137.143
 
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A Novel Image Reconstruction Algorithm Based on Pulse Coupled Neural Network for Electrical Capacitance Tomography System

Shao Lei, Chen Deyun, Gao Ming, Wang Lili, Chen Yu and Yu Xiaoyang

Abstract:
A 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.
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How to cite this article:

Shao Lei, Chen Deyun, Gao Ming, Wang Lili, Chen Yu and Yu Xiaoyang, 2014. A Novel Image Reconstruction Algorithm Based on Pulse Coupled Neural Network for Electrical Capacitance Tomography System. Journal of Applied Sciences, 14: 137-143.

DOI: 10.3923/jas.2014.137.143

URL: https://scialert.net/abstract/?doi=jas.2014.137.143

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