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Articles 1 - 13 of 13
Full-Text Articles in Entire DC Network
Inexact Fixed-Point Proximity Algorithms For Nonsmooth Convex Optimization, Jin Ren
Inexact Fixed-Point Proximity Algorithms For Nonsmooth Convex Optimization, Jin Ren
Mathematics & Statistics Theses & Dissertations
The aim of this dissertation is to develop efficient inexact fixed-point proximity algorithms with convergence guaranteed for nonsmooth convex optimization problems encountered in data science. Nonsmooth convex optimization is one of the core methodologies in data science to acquire knowledge from real-world data and has wide applications in various fields, including signal/image processing, machine learning and distributed computing. In particular, in the context of image reconstruction, compressed sensing and sparse machine learning, either the objective functions or the constraints of the modeling optimization problems are nondifferentiable. Hence, traditional methods such as the gradient descent method and the Newton method are …
Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw
Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw
Electrical & Computer Engineering Theses & Dissertations
Automatic classification of digitally modulated signals is a challenging problem that has traditionally been approached using signal processing tools such as log-likelihood algorithms for signal classification or cyclostationary signal analysis. These approaches are computationally intensive and cumbersome in general, and in recent years alternative approaches that use machine learning have been presented in the literature for automatic classification of digitally modulated signals. This thesis studies deep learning approaches for classifying digitally modulated signals that use deep artificial neural networks in conjunction with the canonical representation of digitally modulated signals in terms of in-phase and quadrature components. Specifically, capsule networks are …
Chen-Fliess Series For Linear Distributed Systems, Natalie T. Pham
Chen-Fliess Series For Linear Distributed Systems, Natalie T. Pham
Electrical & Computer Engineering Theses & Dissertations
Distributed systems like fluid flow and heat transfer are modeled by partial differential equations (PDEs). In control theory, distributed systems are generally reformulated in terms of a linear state space realization, where the state space is an infinite dimensional Banach space or Hilbert space. In the finite dimension case, the input-output map can always be written in terms of a Chen-Fliess functional series, that is, a weighted sum of iterated integrals of the components of the input function. The Chen-Fliess functional series has been used to describe interconnected nonlinear systems, to solve system inversion and tracking problems, and to design …
A Super Fast Algorithm For Estimating Sample Entropy, Weifeng Liu, Ying Jiang, Yuesheng Xu
A Super Fast Algorithm For Estimating Sample Entropy, Weifeng Liu, Ying Jiang, Yuesheng Xu
Mathematics & Statistics Faculty Publications
: Sample entropy, an approximation of the Kolmogorov entropy, was proposed to characterize complexity of a time series, which is essentially defined as − log(B/A), where B denotes the number of matched template pairs with length m and A denotes the number of matched template pairs with m + 1, for a predetermined positive integer m. It has been widely used to analyze physiological signals. As computing sample entropy is time consuming, the box-assisted, bucket-assisted, x-sort, assisted sliding box, and kd-tree-based algorithms were proposed to accelerate its computation. These algorithms require O(N2) or …
Wittgenstein On Miscalculation And The Foundations Of Mathematics, Samuel J. Wheeler
Wittgenstein On Miscalculation And The Foundations Of Mathematics, Samuel J. Wheeler
Philosophy Faculty Publications
In Remarks on the Foundations of Mathematics, Wittgenstein notes that he has 'not yet made the role of miscalculating clear' and that 'the role of the proposition: "I must have miscalculated"...is really the key to an understanding of the "foundations" of mathematics.' In this paper, I hope to get clear on how this is the case. First, I will explain Wittgenstein's understanding of a 'foundation' for mathematics. Then, by showing how the proposition 'I must have miscalculated' differentiates mathematics from the physical sciences, we will see how this proposition is the key to understanding the foundations of mathematics.
On The Geometry Of The Multiplier Space Of ℓPA, Christopher Felder, Raymond Cheng
On The Geometry Of The Multiplier Space Of ℓPA, Christopher Felder, Raymond Cheng
Mathematics & Statistics Faculty Publications
For p ∊ (1, ∞)\ {2}, some properties of the space Mp of multipliers on ℓpA are derived. In particular, the failure of the weak parallelogram laws and the Pythagorean inequalities is demonstrated for Mp. It is also shown that extremal multipliers on the ℓpA spaces are exactly the monomials, in stark contrast to the p = 2 case.
Cloud Ripple Pattern, John Adam
Cloud Ripple Pattern, John Adam
Mathematics & Statistics Faculty Publications
No abstract provided.
Solutions For Fermi Questions, October 2022 Cloud Ripple Pattern, John Adam
Solutions For Fermi Questions, October 2022 Cloud Ripple Pattern, John Adam
Mathematics & Statistics Faculty Publications
No abstract provided.
Robust Testing Of Paired Outcomes Incorporating Covariate Effects In Clustered Data With Informative Cluster Size, Sandipan Dutta
Robust Testing Of Paired Outcomes Incorporating Covariate Effects In Clustered Data With Informative Cluster Size, Sandipan Dutta
Mathematics & Statistics Faculty Publications
Paired outcomes are common in correlated clustered data where the main aim is to compare the distributions of the outcomes in a pair. In such clustered paired data, informative cluster sizes can occur when the number of pairs in a cluster (i.e., a cluster size) is correlated to the paired outcomes or the paired differences. There have been some attempts to develop robust rank-based tests for comparing paired outcomes in such complex clustered data. Most of these existing rank tests developed for paired outcomes in clustered data compare the marginal distributions in a pair and ignore any covariate effect on …
A Drop In The Bucket?: Solutions For Fermi Questions, December 2022, John Adam
A Drop In The Bucket?: Solutions For Fermi Questions, December 2022, John Adam
Mathematics & Statistics Faculty Publications
No abstract provided.
Rock Paintings, John Adam
Rock Paintings, John Adam
Mathematics & Statistics Faculty Publications
No abstract provided.
Recent Analytic Development Of The Dynamic Q-Tensor Theory For Nematic Liquid Crystals, Xiang Xu
Recent Analytic Development Of The Dynamic Q-Tensor Theory For Nematic Liquid Crystals, Xiang Xu
Mathematics & Statistics Faculty Publications
Liquid crystals are a typical type of soft matter that are intermediate between conventional crystalline solids and isotropic fluids. The nematic phase is the simplest liquid crystal phase, and has been studied the most in the mathematical community. There are various continuum models to describe liquid crystals of nematic type, and Q-tensor theory is one among them. The aim of this paper is to give a brief review of recent PDE results regarding the Q-tensor theory in dynamic configurations.
Rock Paintings: Solutions For Fermi Questions, September 2022, John Adam
Rock Paintings: Solutions For Fermi Questions, September 2022, John Adam
Mathematics & Statistics Faculty Publications
No abstract provided.