Dynamical Systems Commons™

All Articles in Dynamical Systems

267 full-text articles. Page 1 of 11.

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.

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.

Learning And Control Using Gaussian Processes, 2017 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 ...

2017 The Graduate Center, City University of New York

Asymptotic Counting Formulas For Markoff-Hurwitz Tuples, Ryan Ronan

All Graduate Works by Year: 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 ...

2017 The Graduate Center, City University of New York

Morphogenesis And Growth Driven By Selection Of Dynamical Properties, Yuri Cantor

All Graduate Works by Year: Dissertations, Theses, and Capstone Projects

Organisms are understood to be complex adaptive systems that evolved to thrive in hostile environments. Though widely studied, the phenomena of organism development and growth, and their relationship to organism dynamics is not well understood. Indeed, the large number of components, their interconnectivity, and complex system interactions all obscure our ability to see, describe, and understand the functioning of biological organisms.

Here we take a synthetic and computational approach to the problem, abstracting the organism as a cellular automaton. Such systems are discrete digital models of real-world environments, making them more accessible and easier to study then their physical world ...

A Real Options Approach To Criminal Careers, 2017 FURG and PPGOM/UFPel

A Real Options Approach To Criminal Careers, Cristiano Aguiar De Oliveira, Giácomo Balbinotto Neto

The Latin American and Iberian Journal of Law and Economics

This paper proposes a dynamic model based on real options to evaluate the criminal career. In the model, individuals can choose the best moment to engage in crime (illegal activity). The model proposed allows the evaluation of the impact of different risk preferences, punishment probability, punishment severity and, mainly time discount in the individual’s decision. Through model calibration it is possible to observe that the option for a criminal career depends on a high return in the illegal activity even when individuals are risk neutral and when they have a low time discount. The paper also discusses youth participation ...

Modeling Economic Systems As Locally-Constructive Sequential Games, 2017 Iowa State University

Modeling Economic Systems As Locally-Constructive Sequential Games, Leigh Tesfatsion

Economics Working Papers

Real-world economies are open-ended dynamic systems consisting of heterogeneous interacting participants. Human participants are decision-makers who strategically take into account the past actions and potential future actions of other participants. All participants are forced to be locally constructive, meaning their actions at any given time must be based on their local states; and participant actions at any given time affect future local states. Taken together, these properties imply real-world economies are locally-constructive sequential games. This study discusses a modeling approach, agent-based computational economics (ACE), that permits researchers to study economic systems from this point of view. ACE modeling principles and ...

2017 University of Leeds

On The Analysis Of The Sir Epidemic Model For Small Networks: An Application In Hospital Settings, Martin Lopez-Garcia

Biology and Medicine Through Mathematics Conference

No abstract provided.

2017 State University of New York at New Paltz

Balanced Excitation And Inhibition Shapes The Dynamics Of A Neuronal Network For Movement And Reward, Anca R. Radulescu

Biology and Medicine Through Mathematics Conference

No abstract provided.

Models Of Nation-Building Via Systems Of Differential Equations, 2017 Cedarville University

Models Of Nation-Building Via Systems Of Differential Equations, Carissa F. Slone, Darryl K. Ahner, Mark E. Oxley, William P. Baker

The Research and Scholarship Symposium

Nation-building modeling is an important field of research given the increasing number of candidate nations and the limited resources available. A modeling methodology and a system of differential equations model are presented to investigate the dynamics of nation-building. The methodology is based upon parameter identification techniques applied to a system of differential equations, to evaluate nation-building operations. Data from Operation Iraqi Freedom (OIF) and Afghanistan are used to demonstrate the validity of different models as well as the comparison of models.

The Battle Against Malaria: A Teachable Moment, 2017 Schoolcraft College

The Battle Against Malaria: A Teachable Moment, Randy K. Schwartz

Journal of Humanistic Mathematics

Malaria has been humanity’s worst public health problem throughout recorded history. Mathematical methods are needed to understand which factors are relevant to the disease and to develop counter-measures against it. This article and the accompanying exercises provide examples of those methods for use in lower- or upper-level courses dealing with probability, statistics, or population modeling. These can be used to illustrate such concepts as correlation, causation, conditional probability, and independence. The article explains how the apparent link between sickle cell trait and resistance to malaria was first verified in Uganda using the chi-squared probability distribution. It goes on to ...

Data Predictive Control For Building Energy Management, 2017 University of Pennsylvania

Data Predictive Control For Building Energy Management, Achin Jain, Madhur Behl, Rahul Mangharam

Real-Time and Embedded Systems Lab (mLAB)

Decisions on how to best optimize energy systems operations are becoming ever so complex and conflicting, that model-based predictive control (MPC) algorithms must play an important role. However, a key factor prohibiting the widespread adoption of MPC in buildings, is the cost, time, and effort associated with learning first-principles based dynamical models of the underlying physical system. This paper introduces an alternative approach for implementing finite-time receding horizon control using control-oriented data-driven models. We call this approach Data Predictive Control (DPC). Specifically, by utilizing separation of variables, two novel algorithms for implementing DPC using a single regression tree and with ...

2017 University of Kentucky

Orbital Stability Results For Soliton Solutions To Nonlinear Schrödinger Equations With External Potentials, Joseph B. Lindgren

Theses and Dissertations--Mathematics

For certain nonlinear Schroedinger equations there exist solutions which are called solitary waves. Addition of a potential $V$ changes the dynamics, but for small enough $||V||_{L^\infty}$ we can still obtain stability (and approximately Newtonian motion of the solitary wave's center of mass) for soliton-like solutions up to a finite time that depends on the size and scale of the potential $V$. Our method is an adaptation of the well-known Lyapunov method.

For the sake of completeness, we also prove long-time stability of traveling solitons in the case $V=0$.

Renewable Energy And Sustainable Development (Resd) Group, 2016 Wroclaw University of Technology

Renewable Energy And Sustainable Development (Resd) Group, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.

Abstract Template Resrb 2018, 2016 Wojciech Budzianowski Consulting Services

Abstract Template Resrb 2018, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.

C.V. - Wojciech Budzianowski, 2016 Wojciech Budzianowski Consulting Services

C.V. - Wojciech Budzianowski, Wojciech M. Budzianowski

Wojciech Budzianowski

-

Call For Abstracts - Resrb 2018, June 18-20, Brussels, Belgium, 2016 Wojciech Budzianowski Consulting Services

Call For Abstracts - Resrb 2018, June 18-20, Brussels, Belgium, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.