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 55 for “"Distance measure"”.
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A Feature-Based Call Graph Distance Measure for Program Similarity Analysis
A measurement for how similar (or distant) two computer programs are has a wide range of possible applications. For example, they can be applied to malware analysis or analysis of university students' programming exercises. However, as programs may be arbitrarily structured, capturing the …
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Audio coding and identification for an interactive television application
… them. The correlation coefficient is used as a distance measure in our IVDS application and compared on the basis of feasibility to other distance measures that have recently been used in the related problems of speech recognition and speaker identity verification. The performance of a few …
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Quantifying balance for casual inference: An information theoretic perspective
… to answer. It is argued that various balance measures used to assess balance in the literature capture different aspects of balance. Measures that utilize only the first two moments may be ignoring information that affect bias and robustness of treatment effect estimates. Additionally, it is …
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FOURTH MOMENT AND SIMULATED POWERS OF MRPP STATISTICS.
… (delta) is simply a weighted average of some distance measure between pairs of observations within a group. It tests H(,0): Classification of data into g groups is random against H(,1): Classification is done according to some a priori scheme. Special cases of (delta) are equivalent to some …
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Distillation and simulation in quantum information
… can usually be characterized by the minimum distance to a set of useless resources under a proper distance measure. We give such characterization for all the tasks studied in this thesis, and find that the distance measure for the distillation and simulation process naturally corresponds to …
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Symbolic clustering
… to be expressed in the choice of a pairwise distance measure and in the choice of clustering algorithm. Conceptual clustering adds knowledge and preferences about cluster descriptions. In this dissertation, I describe symbolic clustering, which adds representation choice to the set of ways a …
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Dynamic Time Warping Constraints for Semiconductor Processing
… new step-constrained DTW is also extended as a distance measure for clustering time series.
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Effects of discrete wavelet compression on automated mammographic shape recognition
… dimensional compression is done on the radial distance measure and the shape features are extracted. Second, linear discriminant analysis is used to compute the weightings of the features. Third, a minimum distance Euclidean classifier and the leave-one-out test method is used for …
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Genetic diversity of midwestern oat germplasm
… variance were calculated 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 …
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Essays on Maximum Entropy Principle With Applications to Econometrics and Finance
… maximum entropy (ME) principle. Since an entropy measure turns out to be a distance measure between two distributions, it can be used to estimate unknown density function. Entropy can be also interpreted as a measure of the degree of diversification and thus provides an useful way to construct …
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Model-Order Reduction Techniques for Circuits and Interconnects Simulation
… lines. A pole-clustering technique with inverse distance-measure criterion is used to further reduce the models. This allows the efficient accurate simulation of frequency-dependent coupled transmission lines characterized by scattering parameters and an optimal reference system. The …
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A population Monte Carlo approach to estimating parametric bidirectional reflectance distribution functions through Markov random field parameter estimation
… methods. A variety of probabilistic distances between these features, including the Kullback-Leibler divergence, the Bhattacharyya distance and the Patrick-Fisher distance is used to test the classifiability of the materials, using the PMC evolved sample sets as features. In our …
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Problems in Pedigrees and Phylogenies
… function that does not use standard evolutionary distances. Instead, we use a distance measure that considers the sequence data simultaneously with substitution model parameters, the topology, and branch lengths of the phylogenetic tree.
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Automated mammographic mass shape classification using wavelets and neural networks
… a wavelet transform was applied to the radial distance measure (RDM) of the mass shapes to obtain multiscale decomposition. The discrete wavelet transform and wavelet packet decompositions were investigated. The second step was the computation of scalar-energy features from the wavelet …
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Feature selection from huge feature sets in the context of computer vision
… features and use correlation as the distance measure for K-means.
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Framework for Automatic Identification of Paper Watermarks with Chain Codes
… and image matching. The development of a novel distance measure for CC comparison is also presented. Examples for the complete process are given using the recently acquired watermarks digitized with hyper-spectral imaging of Summa Theologica, the work of Antonino Pierozzi (1389 – 1459). The …
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An assessment of the application of cluster analysis techniques to the Johannesburg Stock Exchange
… 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 Johannesburg Stock …
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A Mixed-Methods Approach to Force Estimation in Military Operations Other Than War
… mixed-methods approach which uses a multivariate distance measure in order to determine which military operations are similar to each other. Using this information, a researcher can identify similar cases for focused comparison, allowing for both qualitative and quantitative improvements in force …
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An improved self organizing map using jaccard new measure for textual bugs data clustering
… on textual bugs’ data by using two different distance measure which are Euclidean distance and Jaccard New Measure. The research results suggested that SOM has a limitation of poor performance on sparse data set. Thus, the research introduced the improved SOM algorithm by using a Jaccard NM …
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Cellular diagnostic systems using hidden Markov models
… by fitting models to various time-series data measured throughout the network. By including HMMs in the network management tool, a provider can explore the statistical relationships between channel dynamics endemic to a cell and its resulting performance. This research effort also includes a …
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