Browsing Applied mathematics by Title
Now showing items 82-101 of 117
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Reduced Order Model for Global Atmospheric Chemistry Data
Global atmospheric chemistry is an exceptionally high-dimensional problem as it involves hundreds of chemical species that are coupled with each other via a set of ordinary differential equations. Models of atmospheric ... -
Representations in Biological and Artificial Neural Networks
Remarkably, artificial neural networks (ANNs) have shown astounding success in almost all aspects of artificial intelligence. Meanwhile, large scale experiments have gathered an unprecedented amount of data about the ... -
Reproducing color images with custom inks
(1998)This dissertation investigates the general problem of reproducing color images on an off-set printing press using custom inks in any combination and number. Many mathematical and algorithmic challenges arise when printing ... -
Revealing structure in trained neural networks through dimensionality-based methods
Neural networks trained by machine learning optimization methods are currently being analyzed to shed light on brain function. While exciting progress is being made, the complicated nature of the network models typically ... -
Riemann-Hilbert Problems, Their Numerical Solution and the Computation of Nonlinear Special Functions
(2013-11-14)The computation of special functions has important implications throughout engineering and the physical sciences. Nonlinear special functions include the solutions of integrable partial differential equations and the ... -
Robust Approaches for Unsupervised Learning
Today, data science and machine learning are a cornerstone in the engineering, physical, social, and biological sciences. Often, the data available in these fields is large and unlabeled, motivating the development of ... -
Robust dynamic optimization: theory and applications
Many applications in decision-making use a dynamic optimization framework to model a system evolving uncertainly in discrete time, and an agent who chooses actions/controls from a set of available choices in order to ... -
Robust Modeling and Algorithm Design for Science and Engineering
Efficiently extracting information from data sets is at the core of modern scientific com- puting and data-driven discovery. Modeling and algorithm design thus become crucial for research in many scientific and engineering ... -
Robust Real-Time Image Processing Through Dynamic Mode Decomposition
(2013-11-14)In many areas of research, robust and efficient data-mining, and data-driven modeling, have become essential to progressing our understanding of increasingly complex and nonlinear relations often embedded in cluttered ... -
Self-Optimizing Metamaterial Antennas
The reconfigurable holographic metamaterial antenna is an attractive new technology for satellite communications, particularly in mobile applications. This antenna is thin, light-weight, consumes little power to operate, ... -
Single-column and mixed-layer model analysis of subtropical stratocumulus response mechanisms relevant to climate change
(2013-11-14)Subtropical stratocumulus clouds are important part of the Earth's energy budget. The response of low clouds to Earth's changing climate is one of the dominant uncertainties in global warming projections, due primarily ... -
Skew-t Information Matrix: Evaluation and Use
Azzalini’s skew-t distributions, described in detail in Azzalini [2013], have become very popular because of their practical usefulness and the complete R package sn for skew-normal distributions that include extensive ... -
Some Boundary-Value Problems for Water Waves
(2012-09-13)Euler's equations describe the evolution of waves on the surface of an ideal incompressible fluid. In this dissertation, I discuss some boundary-value problems associated with Euler's equations. My approach is motivated ... -
Some Problems in Stochastic Dynamics and Statistical Analysis of Single-Cell Biology of Cancer
With the development of experimental apparatus and data processing softwares, one now has easy access to cancer related data on a single cell, its genome and/or molecular compositions. At this level of description, ... -
Spectral Methods for Partial Differential Equations that Model Shallow Water Wave Phenomena
Mathematical models for waves on shallow water surfaces has been of interest to researchers dating back to the 1800's. These models are governed by partial differential equations, and many of them have rich mathematical ... -
A splitting algorithm for multistage stochastic programming with application to hydropower scheduling
(1997)With water in short supply and utility deregulation imminent, the problem of long-term scheduling on a hydroelectric power system has become increasingly important.Many of the algorithms developed for this large-scale ... -
Stability of solutions of integrable partial differential equations
Stability analysis for solutions of partial differential equations (PDEs) is important for determining the applicability of a model to the physical world. Establishing stability for PDE solutions is often significantly ... -
Statistical, Stochastic, and Dynamical Models of Neural Decision Making
(2013-02-25)Models of decision making provide a direct link between behavior and neurobiology. How does the encoding and accumulation of evidence by neural circuits impact decision making performance? Through data-driven and ... -
Stochastic Control Methods for Dynamic Futures Portfolios
In this thesis, we discuss systematic methods to futures trading and analyze the mathematical problems that arise from trading futures. Firstly, we analyze the dynamic futures trading strategies under a general multifactor ... -
Stochastic Dynamics: Markov Chains, Random Transformations and Applications
Stochastic dynamical systems, as a rapidly growing area in applied mathematics, has been a successful modeling framework for biology, chemistry and data science. Depending upon the origin of uncertainties in an application ...