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Showing 1 to 4 of 4 for “"Stochastic modeling framework"”.

  1. Stochastic Modeling of Micro-Electromechanical Systems (Mems)

    In the final part, a data-driven stochastic collocation approach is presented, which seeks to characterize uncertain input parameters based on available experimental information. This approach models the uncertain parameters as independent random variables, for which the distributions are estimated …

    uiuc Repository record for Stochastic Modeling of Micro-Electromechanical Systems (Mems) (opens in a new tab)

  2. Algebraic Methods for Modeling Gene Regulatory Networks

    … This thesis discusses algebraic methods for modeling and analysis of gene regulatory networks within the discrete modeling context. The first chapter gives a background for discrete models and put in context some of the main research problems that have been pursued in this field for the last …

    vt Repository record for Algebraic Methods for Modeling Gene Regulatory Networks (opens in a new tab)

  3. M/NEM devices and uncertainty quantification

    Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01

    uiuc Repository record for M/NEM devices and uncertainty quantification (opens in a new tab)

  4. Internal multiscale autoregressive processes, stochastic realization, and covariance extension

    … of multiscale autoregressive (MAR) models for stochastic processes from second-order statistical characterizations. The class of MAR processes constitutes a rich and powerful stochastic modeling framework that admits efficient statistical inference algorithms. To harness the utility of MAR …

    mit Repository record for Internal multiscale autoregressive processes, stochastic realization, and covariance extension (opens in a new tab)