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dc.contributor.advisorHuelsman, Lawrence P.en_US
dc.contributor.authorBhalala, Ashesh, 1964-
dc.creatorBhalala, Ashesh, 1964-en_US
dc.date.accessioned2013-03-28T10:23:39Zen
dc.date.available2013-03-28T10:23:39Zen
dc.date.issued1989en_US
dc.identifier.urihttp://hdl.handle.net/10150/276957en
dc.description.abstractSeveral methods to solve a system of linear equations with real and complex coefficients exist. The most popular methods are Gauss-Jordan, L-U Decomposition, Gauss-Seidel, and Matrix Reduction. These methods are utilized to optimize run-time of the DLANET circuit analysis program. As concluded by this study, the Matrix Reduction method which is presently utilized in the DLANET program, results in run-times which are faster than the other solution methods studied in this paper for lower order systems. Similarly, the L-U Decomposition and Gauss-Jordan methods result in faster run-times than the other techniques for higher order systems. Finally, the Gauss-Seidel Iterative method, when incorporated into the DLANET program, has proven to be much slower than the other solution methods considered in this paper.
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectIntegrated circuits -- Computer simulation.en_US
dc.subjectEquations, Simultaneous.en_US
dc.subjectEquations -- Numerical solutions.en_US
dc.titleNumerical solution algorithms in the DLANET programen_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.identifier.oclc22852907en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
dc.identifier.proquest1336543en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.nameM.S.en_US
dc.identifier.bibrecord.b17510582en_US
refterms.dateFOA2018-06-11T18:04:44Z
html.description.abstractSeveral methods to solve a system of linear equations with real and complex coefficients exist. The most popular methods are Gauss-Jordan, L-U Decomposition, Gauss-Seidel, and Matrix Reduction. These methods are utilized to optimize run-time of the DLANET circuit analysis program. As concluded by this study, the Matrix Reduction method which is presently utilized in the DLANET program, results in run-times which are faster than the other solution methods studied in this paper for lower order systems. Similarly, the L-U Decomposition and Gauss-Jordan methods result in faster run-times than the other techniques for higher order systems. Finally, the Gauss-Seidel Iterative method, when incorporated into the DLANET program, has proven to be much slower than the other solution methods considered in this paper.


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