Now showing items 53-72 of 110

• #### Markov chain mixting time, card shuffling and spin systems dynamics ﻿

(2013-07-25)
The mixing time of a Markov chain describes how fast the Markov chain converges to its stationary distribution. In this thesis, we survey some of the knowledge and main tools available in this field by looking at examples. ...
• #### Markov partitions for hyperbolic toral automorphisms ﻿

(1992)
The study of the dynamical properties of hyperbolic toral automorphisms is simplified when the automorphisms are represented as shifts of finite type. The conventional method used to represent such an automorphism symbolically ...
• #### Mathematical Aspects of Gerrymandering ﻿

(2013-11-14)
Every 10 years the United States performs a census, and this census determines how many members of congress will represent each state. Then begins an unfortunate battle, as cartographers manipulate the boundaries for ...
• #### Matrix free methods for large scale optimization ﻿

Sequential quadratic optimization (SQP) methods are widely used to solve large-scale nonlinear optimization problems. We build two matrix-free methods for approximately solving exact penalty subproblems that arise when ...
• #### Non-interior path-following methods for complementarity problems ﻿

(1998)
Because of its excellent numerical performance, non-interior path following methods (also called smoothing methods) have become an important class of methods for solving complementarity problems. However, no rate of ...

• #### On the mod 2 general linear group homology of totally real number rings ﻿

(1997)
We study the mod 2 homology of the general linear group of rings of integers in totally real number fields. In particular, for certain such rings R, we construct a space JKR and show that the mod 2 homology of JKR is a ...
• #### The Ornstein-Uhlenbeck Process In Neural Decision-Making: Mathematical Foundations And Simulations Suggesting The Adaptiveness Of Robustly Integrating Stochastic Neural Evidence ﻿

(2013-02-25)
This master's thesis reviews the concepts behind a stochastic process known as the Ornstein-Uhlenbeck Process, and then uses that process as a way to investigate neural decision making. In particular, MATLAB simulations ...