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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Bases And Applications Of Riemann-Roch Spaces Of Function Fields With Many Rational Places, Justin Peachey
Bases And Applications Of Riemann-Roch Spaces Of Function Fields With Many Rational Places, Justin Peachey
All Dissertations
Algebraic geometry codes are generalizations of Reed-Solomon codes, which are implemented in nearly all digital communication devices. In ground-breaking work, Tsfasman, Vladut, and Zink showed the existence of a sequence of algebraic geometry codes that exceed the Gilbert-Varshamov bound, which was previously thought unbeatable. More recently, it has been shown that multipoint algebraic geometry codes can outperform comparable one-point algebraic geometry codes. In both cases, it is desirable that these function fields have many rational places. The prototypical example of such a function field is the Hermitian function field which is maximal. In 2003, Geil produced a new family of …
Fractal Jackson Networks, Mahmoud Rezaei
Fractal Jackson Networks, Mahmoud Rezaei
All Dissertations
In this dissertation, Gaussian random measures that arise as limits of Jackson networks. The support of the random measure is a fractal having Hausdorff dimension delta . The variance measure is the Hausdorff measure also of dimension delta.
Pseudocodewords Of Parity-Check Codes, Wittawat Kositwattanarerk
Pseudocodewords Of Parity-Check Codes, Wittawat Kositwattanarerk
All Dissertations
The success of modern algorithms for the decoding problem such as message-passing iterative decoding and linear programming decoding lies in their local nature. This feature allows the algorithms to be extremely fast and capable of correcting more errors than guaranteed by the classical minimum distance of the code. Nonetheless, the performance of these decoders depends crucially on the Tanner graph representation of the code. In order to understand this choice of representation, we need to analyze the pseudocodewords of the Tanner graph of a code. These pseudocodewords are outputs of local decoding algorithms which may not be legitimate codewords. In …
Inference In Reversible Markov Chains, Tara Steuber
Inference In Reversible Markov Chains, Tara Steuber
All Dissertations
This dissertation describes the research that we have done concerning
reversible Markov chains. We first present definitions for what it means
for a Markov chain to be reversible. We then give applications of where
reversible Markov chains are used and give a brief history of Markov chain
inference. Finally, two journal articles are found in the paper, one that
is already published and another which is currently being submitted.
The first article examines estimation of the one-step-ahead
transition probabilities in a reversible Markov chain on a countable state
space. A symmetrized moment estimator is proposed that exploits the
reversible structure. …
Multivalued Subsets Under Information Theory, Indraneel Dabhade
Multivalued Subsets Under Information Theory, Indraneel Dabhade
All Theses
In the fields of finance, engineering and varied sciences, Data Mining/ Machine Learning has held an eminent position in predictive analysis. Complex algorithms and adaptive decision models have contributed towards streamlining directed research as well as improve on the accuracies in forecasting. Researchers in the fields of mathematics and computer science have made significant contributions towards the development of this field. Classification based modeling, which holds a significant position amongst the different rule-based algorithms, is one of the most widely used decision making tools. The decision tree has a place of profound significance in classification-based modeling. A number of heuristics …
Optimal Currents In Electrical Impedance Tomography With Robin Boundary Conditions, Cristoffer Cordes
Optimal Currents In Electrical Impedance Tomography With Robin Boundary Conditions, Cristoffer Cordes
All Theses
Electrical Impedance Tomography is an imaging technique with high potential in medical imaging. As of today the resolution is very low and measurement errors have a huge influence on the result.
In order to improve the results, the currents that are applied to perform the measurements have to be chosen carefully, and the best method to do so has not been found yet. For analytical and numerical convenience the spaces of the currents and voltages are often assumed to be L2. However, recent studies have shown that by introducing spaces that are more involved with the weak formulation of the …
New Algorithms For Computing Groebner Bases, Frank Volny
New Algorithms For Computing Groebner Bases, Frank Volny
All Dissertations
In this thesis, we present new algorithms for computing Groebner bases. The first algorithm, G2V, is incremental in the same fashion as F5 and F5C. At a typical step, one is given a Groebner basis G for an ideal I and any polynomial g, and it is desired to compute a Groebner basis for the new ideal , obtained from I by joining g. Let (I : g) denote the colon ideal of I divided by g. Our algorithm computes Groebner bases for I, g and (I : g) simultaneously. In previous algorithms, S-polynomials that reduce to zero are useless, …
Biologically Relevant Classes Of Boolean Functions, Lori Layne
Biologically Relevant Classes Of Boolean Functions, Lori Layne
All Dissertations
A large influx of experimental data has prompted the development of
innovative computational techniques for modeling and reverse
engineering biological networks. While finite dynamical systems,
in particular Boolean networks, have gained attention as relevant
models of network dynamics, not all Boolean functions reflect the
behaviors of real biological systems. In this work, we focus on two
classes of Boolean functions and study their applicability as
biologically relevant network models: the nested and partially nested
canalyzing functions.
We begin by analyzing the nested canalyzing functions} (NCFs),
which have been proposed as gene regulatory network models due to
their stability properties. We …
Physical Process Models As Regularization Constraints On Geophysical Imaging Problems, Rachel Grotheer
Physical Process Models As Regularization Constraints On Geophysical Imaging Problems, Rachel Grotheer
All Theses
Obtaining accurate images of solute plumes in the subsurface is important to understand site-specific subsurface flow and transport processes. Since image reconstruction is an inverse problem, its ill-posed nature makes obtaining an accurate, high-resolution image difficult. Further, current geophysical methods for plume imaging do not take into account models of the specific process being targeted for imaging.
The main objective of the research is to find a suitable basis that gives a sparse representation of the plume. In future work, we seek to use this basis as a physical constraint during the inversion so as to increase accuracy in imaging. …