dc.contributor.author Radcliffe, Tege dc.date.accessioned 2018-11-08T15:05:51Z dc.date.available 2018-11-08T15:05:51Z dc.date.issued 1999-12 dc.identifier.uri https://hdl.handle.net/11274/10671 dc.description.abstract The purpose of the paper is to investigate the efficiency of two matrix-inverting algorithms that are restricted to positive definite matrices. The selected algorithms are a Guass-Jordan method and a gradient projection optimization scheme. en_US To investigate the efficiency, we will be comparing the two algorithms and the two hardware systems. The primary system is a vonNeumann machine, specifically a PC. The other system is a parallel processor we have designed specifically for matrix inversion and implemented by simulation. The paper begins with a review of some basic results concerning positive definite matrices. Following this review, the paper describes the two mathematical algorithms used to determine the inverse and how they will be implemented on the PC. Next we describe the architecture of the parallel processor that will be used to simulate matrix inversion. Following the description of the parallel processor, the implementation of each algorithm on the parallel system is described. To test the efficiency of the algorithms we apply each to several large positive definite matrices and measure the time. The paper concludes with the results of the efficiency study in which each algorithm is compared on the selected system and each system is compared for the selected algorithm. dc.language.iso en_US en_US dc.subject Applied sciences en_US dc.subject Pure sciences en_US dc.subject Mathematics en_US dc.subject Computer science en_US dc.title Inverting a positive definite matrix: A comparative study of two algorithms en_US dc.type Thesis en_US thesis.degree.department Mathematics en_US thesis.degree.grantor Texas Woman's University en_US thesis.degree.level Master en_US thesis.degree.name Master of Science en_US dc.contributor.committeeChair Zimmerman, Wayne
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