Control Theory: The Double Pendulum Inverted On A Cart, 2018 University of New Mexico

#### Control Theory: The Double Pendulum Inverted On A Cart, Ian J P Crowe-Wright

*Mathematics & Statistics ETDs*

In this thesis the Double Pendulum Inverted on a Cart (DPIC) system is modeled using the Euler-Lagrange equation for the chosen Lagrangian, giving a second-order nonlinear system. This system can be approximated by a linear first-order system in which linear control theory can be used. The important definitions and theorems of linear control theory are stated and proved to allow them to be utilized on a linear version of the DPIC system. Controllability and eigenvalue placement for the linear system are shown using MATLAB. Linear Optimal control theory is likewise explained in this section and its uses are applied to ...

Semi-Tensor Product Representations Of Boolean Networks, 2018 Illinois State University

#### Semi-Tensor Product Representations Of Boolean Networks, Matthew Macauley

*Annual Symposium on Biomathematics and Ecology: Education and Research*

No abstract provided.

Introducing The Fractional Differentiation For Clinical Data-Justified Prostate Cancer Modelling Under Iad Therapy, 2018 Illinois State University

#### Introducing The Fractional Differentiation For Clinical Data-Justified Prostate Cancer Modelling Under Iad Therapy, Ozlem Ozturk Mizrak

*Annual Symposium on Biomathematics and Ecology: Education and Research*

No abstract provided.

Ideals, Big Varieties, And Dynamic Networks, 2018 Portland State University

#### Ideals, Big Varieties, And Dynamic Networks, Ian H. Dinwoodie

*Mathematics and Statistics Faculty Publications and Presentations*

The advantage of using algebraic geometry over enumeration for describing sets related to attractors in large dynamic networks from biology is advocated. Examples illustrate the gains.

Asymptotic Behavior Of The Random Logistic Model And Of Parallel Bayesian Logspline Density Estimators, 2018 University of Massachusetts Amherst

#### Asymptotic Behavior Of The Random Logistic Model And Of Parallel Bayesian Logspline Density Estimators, Konstandinos Kotsiopoulos

*Doctoral Dissertations*

This dissertation is comprised of two separate projects. The first concerns a Markov chain called the Random Logistic Model. For r in (0,4] and x in [0,1] the logistic map f_{r}(x) = rx(1 - x) defines, for positive integer t, the dynamical system x_{r}(t + 1) = f(x_{r}(t)) on [0,1], where x_{r}(1) = x. The interplay between this dynamical system and the Markov chain x_{r,N}(t) defined by perturbing the logistic map by truncated Gaussian noise scaled by N^{-1/2}, where N -> infinity, is studied. A natural question is ...

Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., 2018 University of Louisville

#### Multi Self-Adapting Particle Swarm Optimization Algorithm (Msapso)., Gerhard Koch

*Electronic Theses and Dissertations*

The performance and stability of the Particle Swarm Optimization algorithm depends on parameters that are typically tuned manually or adapted based on knowledge from empirical parameter studies. Such parameter selection is ineffectual when faced with a broad range of problem types, which often hinders the adoption of PSO to real world problems. This dissertation develops a dynamic self-optimization approach for the respective parameters (inertia weight, social and cognition). The effects of self-adaption for the optimal balance between superior performance (convergence) and the robustness (divergence) of the algorithm with regard to both simple and complex benchmark functions is investigated. This work ...

Physical Applications Of The Geometric Minimum Action Method, 2018 The Graduate Center, City University of New York

#### Physical Applications Of The Geometric Minimum Action Method, George L. Poppe Jr.

*All Dissertations, Theses, and Capstone Projects*

This thesis extends the landscape of rare events problems solved on stochastic systems by means of the \textit{geometric minimum action method} (gMAM). These include partial differential equations (PDEs) such as the real Ginzburg-Landau equation (RGLE), the linear Schroedinger equation, along with various forms of the nonlinear Schroedinger equation (NLSE) including an application towards an ultra-short pulse mode-locked laser system (MLL).

Additionally we develop analytical tools that can be used alongside numerics to validate those solutions. This includes the use of instanton methods in deriving state transitions for the linear Schroedinger equation and the cubic diffusive NLSE.

These analytical solutions ...

Iterative Methods To Solve Systems Of Nonlinear Algebraic Equations, 2018 Western Kentucky University

#### Iterative Methods To Solve Systems Of Nonlinear Algebraic Equations, Md Shafiful Alam

*Masters Theses & Specialist Projects*

Iterative methods have been a very important area of study in numerical analysis since the inception of computational science. Their use ranges from solving algebraic equations to systems of differential equations and many more. In this thesis, we discuss several iterative methods, however our main focus is Newton's method. We present a detailed study of Newton's method, its order of convergence and the asymptotic error constant when solving problems of various types as well as analyze several pitfalls, which can affect convergence. We also pose some necessary and sufficient conditions on the function f for higher order of ...

P-46 A Periodic Matrix Model Of Seabird Behavior And Population Dynamics, 2018 Andrews University

#### P-46 A Periodic Matrix Model Of Seabird Behavior And Population Dynamics, Mykhaylo M. Malakhov, Benjamin Macdonald, Shandelle M. Henson, J. M. Cushing

*Honors Scholars & Undergraduate Research Poster Symposium Programs*

Rising sea surface temperatures (SSTs) in the Pacific Northwest lead to food resource reductions for surface-feeding seabirds, and have been correlated with several marked behavioral changes. Namely, higher SSTs are associated with increased egg cannibalism and egg-laying synchrony in the colony. We study the long-term effects of climate change on population dynamics and survival by considering a simplified, cross-season model that incorporates both of these behaviors in addition to density-dependent and environmental effects. We show that cannibalism can lead to backward bifurcations and strong Allee effects, allowing the population to survive at lower resource levels than would be possible otherwise.

Learning And Control Using Gaussian Processes, 2018 University of Pennsylvania

#### Learning And Control Using Gaussian Processes, Achin Jain, Truong X Nghiem, Manfred Morari, Rahul Mangharam

*Real-Time and Embedded Systems Lab (mLAB)*

Building physics-based models of complex physical systems like buildings and chemical plants is extremely cost and time prohibitive for applications such as real-time optimal control, production planning and supply chain logistics. Machine learning algorithms can reduce this cost and time complexity, and are, consequently, more scalable for large-scale physical systems. However, there are many practical challenges that must be addressed before employing machine learning for closed-loop control. This paper proposes the use of Gaussian Processes (GP) for learning control-oriented models: (1) We develop methods for the optimal experiment design (OED) of functional tests to learn models of a physical system ...

Gradient Estimation For Attractor Networks, 2018 The Graduate Center, City University of New York

#### Gradient Estimation For Attractor Networks, Thomas Flynn

*All Dissertations, Theses, and Capstone Projects*

It has been hypothesized that neural network models with cyclic connectivity may be more powerful than their feed-forward counterparts. This thesis investigates this hypothesis in several ways. We study the gradient estimation and optimization procedures for several variants of these networks. We show how the convergence of the gradient estimation procedures are related to the properties of the networks. Then we consider how to tune the relative rates of gradient estimation and parameter adaptation to ensure successful optimization in these models. We also derive new gradient estimators for stochastic models. First, we port the forward sensitivity analysis method to the ...

Homeomorphisms Of The Sierpinski Carpet, 2018 Bard College

#### Homeomorphisms Of The Sierpinski Carpet, Karuna S. Sangam

*Senior Projects Spring 2018*

The Sierpinski carpet is a fractal formed by dividing the unit square into nine congruent squares, removing the center one, and repeating the process for each of the eight remaining squares, continuing infinitely many times. It is a well-known fractal with many fascinating topological properties that appears in a variety of different contexts, including as rational Julia sets. In this project, we study self-homeomorphisms of the Sierpinski carpet. We investigate the structure of the homeomorphism group, identify its finite subgroups, and attempt to define a transducer homeomorphism of the carpet. In particular, we find that the symmetry groups of platonic ...

Extensions Of The Morse-Hedlund Theorem, 2018 Bucknell University

#### Extensions Of The Morse-Hedlund Theorem, Eben Blaisdell

*Honors Theses*

Bi-infinite words are sequences of characters that are infinite forwards and backwards; for example "...*ababababab*...". The Morse-Hedlund theorem says that a bi-infinite word *f* repeats itself, in at most *n* letters, if and only if the number of distinct subwords of length *n* is at most *n*. Using the example, "...*ababababab*...", there are 2 subwords of length 3, namely "*aba*" and "*bab*". Since 2 is less than 3, we must have that "...*ababababab*..." repeats itself after at most 3 letters. In fact it does repeat itself every two letters. Interestingly, there are many extensions of this theorem to multiple dimensions ...

Distributed Evolution Of Spiking Neuron Models On Apache Mahout For Time Series Analysis, 2017 Cylance, Inc.

#### Distributed Evolution Of Spiking Neuron Models On Apache Mahout For Time Series Analysis, Andrew Palumbo

*Annual Symposium on Biomathematics and Ecology: Education and Research*

No abstract provided.

An Improved Pairwise- Approximation Technique For Studying The Dynamics Of A Probabilistic, Two- State Lattice Model Of Intracellular Cardiac Calcium, 2017 Loyola Marymount University

#### An Improved Pairwise- Approximation Technique For Studying The Dynamics Of A Probabilistic, Two- State Lattice Model Of Intracellular Cardiac Calcium, Robert J. Rovetti

*Annual Symposium on Biomathematics and Ecology: Education and Research*

No abstract provided.

Mathematical Modeling Of Inhibitory Effects On Chemically Coupled Neurons, 2017 Illinois State University

#### Mathematical Modeling Of Inhibitory Effects On Chemically Coupled Neurons, Nathhaniel Harraman, Epaminondas Rosa

*Annual Symposium on Biomathematics and Ecology: Education and Research*

No abstract provided.

Temperature Effects On Neuronal Tonic-To-Bursting Transitions, 2017 Illinois State University

#### Temperature Effects On Neuronal Tonic-To-Bursting Transitions, Manuela Burek, Epaminondas Rosa

*Annual Symposium on Biomathematics and Ecology: Education and Research*

No abstract provided.

A Brief History Of Neuroscience, 2017 Illinois State University

#### A Brief History Of Neuroscience, Zachary Mobille, Epaminondas Rosa

*Annual Symposium on Biomathematics and Ecology: Education and Research*

No abstract provided.

Asymptotic Counting Formulas For Markoff-Hurwitz Tuples, 2017 The Graduate Center, City University of New York

#### Asymptotic Counting Formulas For Markoff-Hurwitz Tuples, Ryan Ronan

*All Dissertations, Theses, and Capstone Projects*

The Markoff equation is a Diophantine equation in 3 variables first studied in Markoff's celebrated work on indefinite binary quadratic forms. We study the growth of solutions to an n variable generalization of the Markoff equation, which we refer to as the Markoff-Hurwitz equation. We prove explicit asymptotic formulas counting solutions to this generalized equation with and without a congruence restriction. After normalizing and linearizing the equation, we show that all but finitely many solutions appear in the orbit of a certain semigroup of maps acting on finitely many root solutions. We then pass to an accelerated subsemigroup of ...

Time Varying Parameter Estimation Scheme For A Linear Stochastic Differential Equation, 2017 Marshall University

#### Time Varying Parameter Estimation Scheme For A Linear Stochastic Differential Equation, Olusegun Michael Otunuga

*Mathematics Faculty Research*

In this work, an attempt is made to estimate time varying parameters in a linear stochastic differential equation. By defining *mk *as the local admissible sample/data observation size at time *tk*, parameters and state at time *tk *are estimated using past data on interval [*tk*−*mk*+1, *tk*]. We show that the parameter estimates at each time *tk *converge in probability to the true value of the parameters being estimated. A numerical simulation is presented by applying the local lagged adapted generalized method of moments (LLGMM) method to the stochastic differential models governing prices of energy commodities and stock ...