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Showing 1 to 14 of 14 for “"Discontinuous functions"”.

  1. Multiplication of Singularity Functions by Discontinuous Functions in Schwartz Distribution Theory

    Made available in DSpace on 2014-12-09T22:17:39Z (GMT). No. of bitstreams: 1 6801845.pdf: 2926703 bytes, checksum: caa010f9ee71fa5c25702a935aa98561 (MD5) Previous issue date: 1967

    uiuc Repository record for Multiplication of Singularity Functions by Discontinuous Functions in Schwartz Distribution Theory (opens in a new tab)

  2. A learning method for the approximation of discontinuous functions for stochastic simulations

    … for approximating simulation outputs that depend discontinuously on input parameters. Our approach focuses on piecewise smooth outputs and involves two stages: first, efficient detection and localization of discontinuities in high-dimensional parameter spaces using polynomial annihilation, support …

    mit Repository record for A learning method for the approximation of discontinuous functions for stochastic simulations (opens in a new tab)

  3. The Asymptotic Behavior of Birkhoff- and Lacunary Sums

    … sums. The former are sums formed by periodic functions and exponentially growing sequences of natural numbers. The corresponding summands often exhibit behavior typical of independent and identically distributed random variables. The methods used are of an analytical and probabilistic nature. …

    passau-thes Repository record for The Asymptotic Behavior of Birkhoff- and Lacunary Sums (opens in a new tab)

  4. Wavelet-Based Statistical Modeling and Image Estimation

    … approximation error when approximating smooth functions, and mitigates Gibbs artifacts when approximating discontinuous functions. Second, we study TI estimators and show that under mild conditions, replacing an estimator with its TI version will not worsen the estimation performance as …

    uiuc Repository record for Wavelet-Based Statistical Modeling and Image Estimation (opens in a new tab)

  5. An Introduction to the Lebesgue Integral

    … of the integral that allows a wider class of functions to be integrated. However, there are many other types of integrals, the most important of which is the Lebesgue integral. The Lebesgue integral allows one to integrate unbounded or discontinuous functions whose Riemann integral does not …

    govst Repository record for An Introduction to the Lebesgue Integral (opens in a new tab)

  6. Representation discovery in non-parametric reinforcement learning

    … that use kernel regression to approximate value functions. The correctness guarantees of kernel regression require that the underlying value function be smooth. Most problems of interest do not satisfy this requirement in their native space, but can be represented in such a way that they do. In …

    mit Repository record for Representation discovery in non-parametric reinforcement learning (opens in a new tab)

  7. Connectivity and Darboux functions

    Electronic Thesis or Dissertation

    alabama Repository record for Connectivity and Darboux functions (opens in a new tab)

  8. Data-Driven Deep Learning Methods for Physically-Based Simulations

    … Network layers: the Graph Informed layer and the Discontinuous layer. The first one is defined to embed Neural Network architectures with graphs and improve prediction abilities on graph-structured data (as the Discrete Fracture Network models). The second one introduces learnable discontinuities …

    poli-torino Repository record for Data-Driven Deep Learning Methods for Physically-Based Simulations (opens in a new tab)

  9. Effect of modal truncation on derivatives of closed-loop damping ratios in structural control

    It is well known that Fourier series of discontinuous functions converge slowly and that the derivatives of the series may not converge at all. Since modal expansion of structural response is a generalization of the Fourier series, slow convergence of modal expansion can be expected when the …

    vt Repository record for Effect of modal truncation on derivatives of closed-loop damping ratios in structural control (opens in a new tab)

  10. Active learning based on a hybrid neural network modeller

    … and interesting when the method is applied to discontinuous functions. Although the experiments are conducted with clean data selection, it should be easy to extend them to noisy data selection since the method developed is validated using unlabelled data. The algorithm developed for these …

    abertay Repository record for Active learning based on a hybrid neural network modeller (opens in a new tab)

  11. On instabilities and trust in deep learning

    … to neural networks’ ability to approximate discontinuous functions. Chapter 4 examines the feasibility of learning uncertainty estimates for models, focusing on the potential to develop methods that help neural networks gauge their own confidence. The chapter introduces ‘shadow properties’, …

    cambridge Repository record for On instabilities and trust in deep learning (opens in a new tab)

  12. Global optimization in reduced space

    … McCormick relaxations is extended to a class of discontinuous functions. It is further shown that branch-and-bound algorithms still possess their convergence properties.

    mit Repository record for Global optimization in reduced space (opens in a new tab)

  13. Developments in the Extended Finite Element Method and Algebraic Multigrid for Solid Mechanics Problems Involving Discontinuities

    In this dissertation, some contributions related to computational modeling and solution of solid mechanics problems involving discontinuities are discussed. The main tool employed for discrete modeling of discontinuities is the extended finite element method and the primary solution method …

    columbia-diss Repository record for Developments in the Extended Finite Element Method and Algebraic Multigrid for Solid Mechanics Problems Involving Discontinuities (opens in a new tab)