Browsing by Subject "Algorithms."
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Item A linked-plane obstacle-set algorithm for modeling broad muscle paths : application to the deltoid muscle.(2008-10-01T19:03:48Z) Xu, Bo, 1984-; Garner, Brian Alan, 1966-; Engineering.; Baylor University. Dept. of Mechanical Engineering.Computer modeling is commonly used to simulate muscle paths for the study of human biomechanics. Because some muscles, such as broad muscles, have complex morphology, modeling the paths of these muscles can be challenging. The aim of this study is to develop a new algorithm that quickly and realistically models the wrapping paths of broad muscles. The algorithm treats the muscle as a series of elastic bands wrapping around sphere-shaped obstacles. Each band is constrained to lie in its own plane and wrap around its own sphere. Each band plane forms a given angle with respect to the adjacent band plane, with the first band plane forming an optimized angle with respect to a fixed reference plane. The optimization seeks to minimize the sum total of all band lengths. The new algorithm accounts for tissue connectivity between muscle fibers in broad muscles, and can reproduce realistic muscle moment arm simulations.Item PG-means: learning the number of clusters in data.(2007-03-19T14:52:48Z) Feng, Yu.; Hamerly, Gregory James, 1977-; Computer Science.; Baylor University. Dept. of Computer Science.We present a novel algorithm called PG-means in this thesis. This algorithm is able to determine the number of clusters in a classical Gaussian mixture model automatically. PG-means uses efficient statistical hypothesis tests on one-dimensional projections of the data and model to determine if the examples are well represented by the model. In so doing, we apply a statistical test to the entire model at once, not just on a per-cluster basis. We show that this method works well in difficult cases such as overlapping clusters, eccentric clusters and high dimensional clusters. PG-means also works well on non-Gaussian clusters and many true clusters. Further, the new approach provides a much more stable estimate of the number of clusters than current methods.Item Restarting the Lanczos algorithm for large eigenvalue problems and linear equations.(2008-10-02T18:39:19Z) Nicely, Dywayne A.; Morgan, Ronald Benjamin, 1958-; Mathematics.; Baylor University. Dept. of Mathematics.We are interested in computing eigenvalues and eigenvectors of large matrices and in solving large systems of linear equations. Restarted versions of both the symmetric and nonsymmetric Lanczos algorithms are given. For the symmetric case, we give a method called Lan-DR that simultaneously solves linear equations and computes eigenvalues and eigenvectors. The use of approximate eigenvectors deflates eigenvalues. Maintaining the orthogonality of the Lanczos vectors is a concern. We suggest an approach that is a combination of Parlett and Scott's idea of selective orthogonalization and Simon's partial orthogonalization. For linear systems with multiple right-sides, eigenvectors computed during the solution of the first right-hand side can be used to give much faster convergence of the second and subsequent right-hand sides. A restarted version of the nonsymmetric Lanczos algorithm is developed. Both the right and left eigenvectors are computed while systems of linear equations are solved. We also investigate a restarted two-sided Arnoldi. We compare expense and stability of this approach with restarted nonsymmetric Lanczos.Item Robust geolocation techniques for multiple receiver systems.(2011-05-12T15:25:52Z) Fisher, Gregory W.; Thompson, Michael Wayne.; Engineering.; Baylor University. Dept. of Electrical and Computer Engineering.The purpose of this thesis is to investigate signal processing algorithms that allow multiple moving receivers to locate a stationary emitter. This problem has received considerable attention over the past 50 years, yet advances in computational power, sensor technologies and increasingly complex battle space scenarios continue to drive interest in this area. This work focuses on implementing well-known least squares and Kalman based algorithms within a realistic three dimensional simulation model. Techniques for evaluating the performance of various algorithms include generating ellipse-shaped confidence regions that bound the target under consideration, along with generating polygon shaped confidence regions based on intersecting regions from multiple receivers. The presence of outlier angle of arrival measurements is shown to significantly degrade the performance of geolocation algorithms. Methods for imparting robustness to outlier angle of arrival measurements are developed and shown to mitigate the corresponding loss in performance that would otherwise occur.Item Towards a systematic investigation of weakly coupled free fermionic heterotic string gauge group statistics.(2009-07-08T18:47:57Z) Robinson, Matthew Brandon, 1981-; Cleaver, Gerald B.; Physics.; Baylor University. Dept. of Physics.We investigate several issues regarding weakly coupled free fermionic heterotic string model building. After reviewing the necessary background, we first address an alternative interpretation of the GSO projection in terms of the Weyl conditions on the root space of the gauge group of a given model. We develop an algorithm to systematically generate and analyze string models very efficiently by linearizing the constraints. Next we investigate free fermionic model building from the approach of quantum computing algorithms. We also consider a few unique and interesting gauge groups which can arise in non-standard ways using this method. Then we develop a variation of the well known “NAHE” basis of (quasi)-realistic models with initial observable sector gauge group SO(10) that offers the possibility of a new class of models with an initial observable sector gauge group of E6. Finally we consider several topics regarding the applications of Optical Unification in string models.