Abstract
In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents two stochastic optimization techniques such as particle swarm optimization (PSO).and simultaneous perturbation stochastic approximation (SPSA) algorithms for solving the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, particle swarm optimization, and simultaneous perturbation stochastic approximation.
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Boo, CJ., Kim, HC., Kang, MJ., Lee, K.Y. (2010). Stochastic Optimization Approaches to Image Reconstruction in Electrical Impedance Tomography. In: Taniar, D., Gervasi, O., Murgante, B., Pardede, E., Apduhan, B.O. (eds) Computational Science and Its Applications – ICCSA 2010. ICCSA 2010. Lecture Notes in Computer Science, vol 6017. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12165-4_8
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DOI: https://doi.org/10.1007/978-3-642-12165-4_8
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