標題: Electrical Impedance Tomography: A Reconstruction Method Based on Neural Networks and Particle Swarm Optimization
作者: Martin, Sebastien
Choi, Charles T. M.
交大名義發表
National Chiao Tung University
關鍵字: Electrical impedance tomography;neural network;particle swarm optimization;finite element method;inverse problems
公開日期: 1-Jan-2015
摘要: Electrical Impedance Tomography (EIT) is a non-invasive image reconstruction technique. Typically, an EIT scheme involves the solution to an inverse problem, which usually gives a poor resolution, due to linearization and ill-posedness of the problem. An alternative approach based on Artificial Neural Networks (ANN) has been used as a replacement of the inverse problem, giving correct results without linearizing the problem. However, training an ANN may be time consuming and usually requires a large amount of iterations before achieving a correct answer to the input stimulation. Several studies focused on training ANNs, and Evolutionary Algorithms (EA) gives a faster global convergence. In this paper, a novel approach based on Artificial Neural Networks and Particle Swarm Optimization (PSO) is proposed to improve the training process. A training method based on PSO algorithm achieves a faster global convergence.
URI: http://dx.doi.org/10.1007/978-3-319-12262-5_49
http://hdl.handle.net/11536/124979
ISBN: 978-3-319-12261-8
ISSN: 1680-0737
DOI: 10.1007/978-3-319-12262-5_49
期刊: 1ST GLOBAL CONFERENCE ON BIOMEDICAL ENGINEERING & 9TH ASIAN-PACIFIC CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING
Volume: 47
起始頁: 177
結束頁: 179
Appears in Collections:Conferences Paper