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 6 of 6 for “"Discrepancy Function"”.
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Automatic simulation-driven reachability using matrix measures
… states converge or diverge. We call this discrepancy function. The algorithms rely on computing local bounds on the matrix measure of the Jacobian matrices. We discuss different techniques to compute the matrix measures under different norms: regular Euclidean norm or Euclidean norm under …
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The Optimal Weighting of Pre-Election Polling Data
… were conducted. Long- and short-memory weight functions are developed to specify the relative value of historical polling data. An optimal weight function is estimated by minimizing the discrepancy function between estimates from weighted polls and the election outcomes.
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Dynamic analysis of Cyber-Physical Systems
… is very important to ensure that these systems function reliably without any failures. While testing improves confidence in these systems, it does not establish the absence of scenarios where the system fails. The focus of this thesis is on formal verification techniques for cyber-physical …
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Distribution of Farey Series and Free Path Lengths for a Certain Billiard in the Unit Square
… sums into expressions involving the Mobius function. In 1924 Franel produced a quantitative form of this equivalence as an identity for the sum of the squares of the values of the local discrepancy function of the Mobius function and related this to the real parts of zeros of the Riemann …
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Physics-Informed, Data-Driven Framework for Model-Form Uncertainty Estimation and Reduction in RANS Simulations
… RANS turbulence modeling is proposed. The functional forms of model discrepancies with respect to mean flow features are extracted from the off-line database of closely related flows based on machine learning algorithms. The RANS-modeled Reynolds stresses of prediction flows can be …
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Preliminary psychometric characteristics of the critical thinking self-assessment scale
… The Maximum Likelihood (ML) estimation-minimum discrepancy function-χ2 values were significant for all six core scales. However, the three model fit scales had a ratio of χ2 to degrees of freedom (CMIN / df) < 2 indicating good model fit. The Null hypothesis “not - close fit” (H0 = Ԑ ≥ 0.05) was …