Thesis (Ph. D.)--Ohio State University, 1978. / Includes vita. Includes bibliographical references (leaves 90-92). Available online via OhioLINK's ETD Center.

Thesis--University of Florida. / Description based on print version record. Typescript. Vita. Bibliography: leaf 510.

Inaug.-diss.--Würzburg. / Vita.

Thesis (M.S.)--University of Florida, 2002. / Title from title page of source document. Document formatted into pages; contains xi, 84 p.; also contains graphics. Includes vita. Includes bibliographical references.

Thesis (Ph.D.). / Written for the School of Computer Science. Title from title page of PDF (viewed 2008/03/12). Includes bibliographical references.

"This paper is a study of finite systems of homogenous linear inequalities, homogeneous linear equations, and nonhomogeneous equations. To each inequality or equation in one system there corresponds a nonnegative or unrestricted variable in the other and conversely. The array of coefficients in one system is the negative transpose in the other system. This duality furnishes the foundation for the duality of matrix games and linear programming"--Introduction. / Typescript. / "June, 1959." / "Submitted to the Graduate Council of Florida State University in partial fulfillment of the requirements for the degree of Master of Science." / Advisor: Paul J. McCarthy, Professor Directing Paper. / Includes bibliographical references (leaves 38-39).

Proefschrift--Nederlandse Economische Hogeschool, Rotterdam. / Text in English, summary and inserted notes in Dutch. Stellingen: [1] p. inserted. Bibliography: p. 105-106.

In this thesis we consider the problem of simultaneously approximating elements of a set B C X by a single element of a set K C X. This type of a problem arises when the element to be approximated is not known precisely but is known to belong to a set.Thus, best simultaneous approximation is a natural generalization of best approximation which has been studied extensively. The theory of best simultaneous approximation has been studied by many authors, see for example [4], [8], [25], [28], [26] and [12] to name but a few.

Several 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.

Thesis (M.A.)--Ohio State University, 1950. / Advisor: John R. Kinzer. Text made available in compliance with Section 108 of the Copyright Revision Act of 1976. Includes bibliographical references (leaves 73-77). Online version of print reproduction.