Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 124 for “"Euclidean distance"”.
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A Squared-Euclidean distance location-allocation problem
none available
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Geographically weighted Regression with non-Euclidean distance metrics
Available with hard copy only.
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Algorithmic Approaches for Solving the Euclidean Distance Location and Location-Allocation Problems
… and location-allocation problems in which the Euclidean metric is used to measure distances. To overcome the nondifferentiability difficulty associated with the Euclidean norm function, specialized solution procedures are developed for both the location and the location-allocation problems. For …
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An Empirical Approach to Evaluating Sufficient Similarity: Utilization of Euclidean Distance As A Similarity Measure
… process. Four similarity measures based on Euclidean distance are developed to aid in the evaluation of sufficient similarity in dose-response, allowing for mixtures to be subsets of each other. If a reference and candidate mixture are concluded to be sufficiently similar in dose-response, …
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Design and testing of a real time simulation for Trellis Coded Modulation
… TCM schemes, soft decision decoding, based on euclidean distance, rather than hard decision decoding, based on hamming distance, is used. Ungerboeck developed a mapping of encoder bits to channel signals on a constellation diagram. The mapping is called mapping by set partitioning and aims to …
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Matrix Factorizations, Triadic Matrices, and Modified Cholesky Factorizations for Optimization
… We apply our modified Newton methods to the Euclidean distance matrix completion problem (EDMCP). Given n points in Euclidean space, the Euclidean distance matrix (EDM) is the real symmetric matrix with (i,j) entry being the square of the Euclidean distance between i-th and j-th points. Given …
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Analyzing Crime on Street Networks: A Comparison of Network and Euclidean Voronoi Methods
… methods that are based on the assumption of Euclidean (straight-line) distance. However, crime like most social activity is often mediated by the built environment, such as along a street or within a multi-story building. Thus, analyzing spatial patterns of crime with only straight-line …
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Genetic diversity of midwestern oat germplasm
… for each mating. Four measures of genetic distance between the parents were calculated: geneological distance, Euclidean distance based upon principal components, and the distance measures proposed by Hanson and Casas and Cervantes et al. The relationships between the four distance measures …
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An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange
… in the data set. Using Ward's method and the Euclidean distance function, this method appears to be able detect the correct number of clusters on the JSE. Second, the ability of three different clustering algorithms to generate consistent clusters and cluster members over time on the …
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Probabilistic Finite Mixture Clustering of Genetic Expression Microarray Data
… observations to the one component for which its Euclidean distance from the center is smallest. Furthermore, these methods force a common variance in every dimension and do not permit covariances between dimensions. A final limitation is that these methods prohibit statistical inference.
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A Comparison of Various Non-Parametric Discriminating Procedures When the Populations Are Bivariate Exponentials
… for each function was very small. However, the Euclidean distance function consistently performed as well as, and sometimes superior to any of the others studied in the this thesis.
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Graphs of integral distance and their properties
… q = pr elements, p prime, where each squared Euclidean distance of two points is a square in Fq: The latter points are said to be at integral distance in Fmq , and the sets above are called integral point sets.
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Vehicle Tracking and Classification via 3D Geometries for Intelligent Transportation Systems
… transform domains (PCA & LDA) using Minimum Euclidean Distance, Maximum Likelihood and Artificial Neural Networks. Additionally, we demonstrate the ability to fuse separate classifiers from multiple domains via Bayesian Networks to achieve ensemble classification.
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An investigation into the performance capabilities of multi-h CPFSK digital modulation
… The Viterbi path metric is given by the squared euclidean distance between the particular path and the received signal.
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Brief Study of Classification Algorithms in Machine Learning
… each algorithm. KNN algorithm is designed using Euclidean distance measurement and Decision Trees make use of ID3 algorithm as a basis. We conclude the study by providing an overall picture of its strengths and weaknesses in solving different types of problems. Also a major point to note is that …
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Channel matched iterative decoding for magnetic recording systems.
… convolutional, to suppress the occurrence of low-Euclidean-distance errors at the output of the channel detector. To understand this mechanism, and with no loss of generality, we derive the error Euclidean distance distribution of TE-EPCC for the Dicode channel, and show that EPCC substantially …
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Spectral discontinuity in concatenative speech synthesis – perception, join costs and feature transformations
… A number of standard speech parametrisations and distance measures were tested as measures of spectral continuity and analysed to identify their limitations. Time-frequency resolution was found to limit the performance of standard speech parametrisations.As a solution to this problem, measures of …
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3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model fitting
… volume resulted in surface-to-surface average distances of 4.28 mm and 3.20 mm, using three and sixteen landmarks respectively. Hence, increasing the number of landmarks produces a posterior model that makes better predictions of patientspecific reconstructions. An average Euclidean distance of …
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Probabilistic formulations of some facility location problems
… of either the expected rectilinear or the Euclidean distance, as well as a quadratic function of the expected Euclidean distance. In the generalized Weber problem the locations of the existing facilities and the item movement between facilities are considered to be random variables. Two …
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