Publication Date

2018

Document Type

Dissertation/Thesis

First Advisor

Krislock, Nathan

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Mathematical Sciences

LCSH

Mathematics

Abstract

In this thesis, our goal is to study the problem of minimizing a polynomial p(x) using semidefinite matrices. Our discussion will cover Lagrangian duality and conic programming, followed by a discussion on how nonnegative polynomials can be approximated by sums of squares. We will use this approximation to create our semidefinite programming problems. This will lead us to being able to solve the problem of wireless coverage using minimum transmission.

Comments

Advisors: Nathan Krislock.||Committee members: Jose Yunier Bello Cruz; Sien Deng.||Includes illustrations.||Includes bibliographical references.

Extent

57 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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