The applications of generalized inverses of matrices appear in many fields like applied mathematics, statistics and engineering [2]. In this thesis, we discuss generalized inverses of matrices over Ore polynomial rings (also called Ore matrices). We first introduce some necessary and sufficient conditions for the existence of {1}-, {1,2}-, {1,3}-, {1,4}- and MP-inverses of Ore matrices, and give some explicit formulas for these inverses. Using {1}-inverses of Ore matrices, we present the solutions of linear systems over Ore polynomial rings. Next, we extend Roth's Theorem 1 and generalized Roth's Theorem 1 to the Ore matrices case. Furthermore, we consider the extensions of all the involutions ψ on R(x), and construct some necessary and sufficient conditions for ψ to be an involution on R(x)[D;σ,δ]. Finally, we obtain two different explicit formulas for {1,3}- and {1,4}-inverses of Ore matrices. The Maple implementations of our main algorithms are presented in the Appendix. / May 2017

No description available.

M.Sc.

by Kim Hung Lo. / Thesis (M.Ph.)--Chinese University of Hong Kong, 1988. / Bibliography: leaf 70.

Thesis (MSc)--Stellenbosch University, 2013. / Please refer to full text to view abstract.

<p>Predmet izučavanja doktorske disertacije jeste postavljanje univerzalne metode za rešavanje fazi linearnih sistema primenom blokovske reprezentacije uopštenih inverza matrice. Pre svega, postavljen je potreban i dovoljan uslov za ekzistenciju rešanja fazi linearnog sistema. Zatim je data tačna algebarska forma rešenja i na kraju je predstavljen efikasan algoritam.</p> / <p>Thе subject of research of thesis is setting universal method for solving fuzzy linear systems using a block representation of generalized inversis of a matrix. A necessary and sufficienf condition for the existence solutions of fuzzy linear systems is given. The exact algebraic form of any solutiof fuzzy linear system is established.</p>

Markov chains are a fundamental subject of study in mathematical probability and have found wide application in nearly every branch of science. Of particular interest are finite-state Markov chains; the representation of finite-state Markov chains by a transition matrix facilitates detailed analysis by linear algebraic methods. Previous methods of analyzing finite-state Markov chains have emphasized state events. In this thesis we develop the concept of a transition event and define two types of transition events: cumulative events and time-average events. Transition events generalize state events and provide a more flexible framework for analysis. We derive computable, closed-form expressions for the expectation of these two events, characterize the conditioning of transition events, provide an algorithm for computing the expectation of these events, and analyze the complexity and stability of the algorithm. As an application, we derive a construction of composite Markov chains, which we use to study competitive dynamics.