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Showing 1 to 20 of 124 for “"Euclidean distance"”.

  1. 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 …

    vt Repository record for Algorithmic Approaches for Solving the Euclidean Distance Location and Location-Allocation Problems (opens in a new tab)

  2. 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, …

    vcu Repository record for An Empirical Approach to Evaluating Sufficient Similarity: Utilization of Euclidean Distance As A Similarity Measure (opens in a new tab)

  3. 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 …

    cape-town Repository record for Design and testing of a real time simulation for Trellis Coded Modulation (opens in a new tab)

  4. 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 …

    maryland Repository record for Matrix Factorizations, Triadic Matrices, and Modified Cholesky Factorizations for Optimization (opens in a new tab)

  5. 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 …

    uiuc Repository record for Analyzing Crime on Street Networks: A Comparison of Network and Euclidean Voronoi Methods (opens in a new tab)

  6. 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 …

    iastate Repository record for Genetic diversity of midwestern oat germplasm (opens in a new tab)

  7. 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 …

    cape-town Repository record for An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange (opens in a new tab)

  8. 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.

    wfu Repository record for Probabilistic Finite Mixture Clustering of Genetic Expression Microarray Data (opens in a new tab)

  9. 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.

    nps Repository record for A Comparison of Various Non-Parametric Discriminating Procedures When the Populations Are Bivariate Exponentials (opens in a new tab)

  10. 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.

    western-cape Repository record for Graphs of integral distance and their properties (opens in a new tab)

  11. 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.

    ucf

  12. 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.

    cape-town Repository record for An investigation into the performance capabilities of multi-h CPFSK digital modulation (opens in a new tab)

  13. 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 …

    cuny Repository record for Brief Study of Classification Algorithms in Machine Learning (opens in a new tab)

  14. 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 …

    umn Repository record for Channel matched iterative decoding for magnetic recording systems. (opens in a new tab)

  15. 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 …

    dcu Repository record for Spectral discontinuity in concatenative speech synthesis – perception, join costs and feature transformations (opens in a new tab)

  16. 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 …

    cape-town Repository record for 3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model fitting (opens in a new tab)

  17. 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 …

    vt Repository record for Probabilistic formulations of some facility location problems (opens in a new tab)

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