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Author Tucker, George ♦ Whittle, Sam ♦ Wang, Ting-You
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Inverse Problem ♦ Numerical Recovery Method ♦ Regularization Term ♦ Large Network ♦ Real Life Situation ♦ Square Lattice ♦ Numerical Differentiation ♦ Symbolic Differentiation ♦ Electrical Network ♦ Square Optimization ♦ Priori Knowledge ♦ Steepest Descent
Abstract Abstract. In this paper, we present the approaches we took to recover the conductances of an electrical network, concentrating on the method of non-linear least squares optimization. The methods include steepest descent with symbolic differentiation and numerical differentiation, Newton’s method, and Levenberg-Marquardt. Using these algorithms, we were able to recover large networks. In order to better reflect real life situations, we decided to add noise to our measurements and include some knowledge of the resistors. This led us to add a regularization term and try a method of rounding between iterations. In the end, without any a priori knowledge, we recovered a 50x50 square lattice
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article