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In this talk, I begin with a review of different geometric flows (PDEs) including mean curvature (curve shortening) flow,surface diffusion flow, Willmore flow, etc., which arise from materials science...
The contribution is part of an interdisciplinary research that aims to address the problems of knowledge, interpretation and documentation of vulnerable structures such as the brick Renaissance domes ...
Recently we assist to an increasing availability of HBIM models rich in geometric and informative terms. Instead, there is still a lack of researches implementing dedicated libraries, based on paramet...
We consider geometric biomembranes governed by an L 2 -gradient flow for bending energy subject to area and volume constraints (Helfrich model). We give a concise derivation of a novel vector...
In this paper we present a robustness study of the two channel echoic parametric demixing problem. More specific, assume an oracle (or a perfect estimator) is providing a truncated estimate of the mix...
We propose a simple time-domain, non-parametric method to estimate the damping at the fundamental frequency of a building. The method aims at obtaining quick-and-dirty data on large sets of buildings,...
Nonlinear parametric excitation refers to the nonlinear analysis of a system of ordinary differential equations with periodic coefficients. In contrast to linear parametric excitation, which offers de...
Non-parametric function estimation aims to estimate or recover or denoise a function of interest, perhaps a signal, spectrum or image, that is observed in noise and possibly indirectly after some tr...
Bayesian Inference and the Parametric Bootstrap。
The paper proposes a segmentation procedure inspired to a robust LIDaR filtering data method recently introduced by the authors. The method is based on the application of a Simultaneous AutoRegressi...
It is shown that robust stability and robust performance questions for control systems with nonparametric uncertainties can be turned into those with a particularly simple parametric description. It i...
The problem of optimizing the H_infinity norm of a rational transfer matrix with respect to a finite number of design parameters is considered. The H_infinity norm is characterized as a value of a par...
A method is presented for parameter set estimation for a system which contains both parametric and nonparametric uncertainty. Prior information is available about both types of uncertainty, but only t...
We consider linear time-invariant systems subject to real, parametric variations. The problem of computing the half-sidelength 1/mu_infinity of the largest stability hypercube in the parameter space i...
A method is presented for parameter set estimation where the system model is assumed to contain both parametric and nonparametric uncertainty. In the disturbance-free case, the parameter set estimate ...

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