The Experts below are selected from a list of 70926 Experts worldwide ranked by ideXlab platform
M C Campi - One of the best experts on this subject based on the ideXlab platform.
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brief non asymptotic confidence ellipsoids for the least squares estimate
Automatica, 2002Co-Authors: Erik Weyer, M C CampiAbstract:In this paper, we consider the finite sample properties of least-squares system identification, and derive non-asymptotic confidence ellipsoids for the estimate. The shape of the confidence ellipsoids is similar to the shape of the ellipsoids derived using asymptotic theory, but unlike asymptotic theory, they are valid for a finite number of data points. The probability that the estimate belongs to a certain ellipsoid has a natural dependence on the volume of the ellipsoid, the data Generating Mechanism, the model order and the number of data points available.
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non asymptotic confidence ellipsoids for the least squares estimate
Conference on Decision and Control, 2000Co-Authors: Erik Weyer, M C CampiAbstract:In this paper we consider the finite sample properties of least squares system identification, and we derive nonasymptotic confidence ellipsoids for the estimate. Unlike asymptotic theory, the obtained confidence ellipsoids are valid for a finite number of data points. The probability that the estimate belongs to a certain ellipsoid has a natural dependence on the volume of the ellipsoid, the data Generating Mechanism, the model order and the number of data points available.
Erik Weyer - One of the best experts on this subject based on the ideXlab platform.
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brief non asymptotic confidence ellipsoids for the least squares estimate
Automatica, 2002Co-Authors: Erik Weyer, M C CampiAbstract:In this paper, we consider the finite sample properties of least-squares system identification, and derive non-asymptotic confidence ellipsoids for the estimate. The shape of the confidence ellipsoids is similar to the shape of the ellipsoids derived using asymptotic theory, but unlike asymptotic theory, they are valid for a finite number of data points. The probability that the estimate belongs to a certain ellipsoid has a natural dependence on the volume of the ellipsoid, the data Generating Mechanism, the model order and the number of data points available.
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non asymptotic confidence ellipsoids for the least squares estimate
Conference on Decision and Control, 2000Co-Authors: Erik Weyer, M C CampiAbstract:In this paper we consider the finite sample properties of least squares system identification, and we derive nonasymptotic confidence ellipsoids for the estimate. Unlike asymptotic theory, the obtained confidence ellipsoids are valid for a finite number of data points. The probability that the estimate belongs to a certain ellipsoid has a natural dependence on the volume of the ellipsoid, the data Generating Mechanism, the model order and the number of data points available.
Bergal-kuvikas Olga - One of the best experts on this subject based on the ideXlab platform.
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Deep long period volcanic earthquakes generated by degassing of volatile-rich basaltic magmas
'Springer Science and Business Media LLC', 2020Co-Authors: Melnik Oleg, Lyakhovsky Vladimir, Shapiro Nikolaï, Galina Natalia, Bergal-kuvikas OlgaAbstract:International audienceDeep long-period (DLP) earthquakes observed beneath active volcanoes are sometimes considered as precursors to eruptions. Their origin remains, however, unclear. Here, we present a possible DLP Generating Mechanism related to the rapid growth of gas bubbles in response to the slow decompression of over-saturated magma. For certain values of the gas and bubble content, the elastic deformation of surrounding rocks forced by the expanding bubbly magma can be fast enough to generate seismic waves. We show that amplitudes and frequencies of DLP earthquakes observed beneath the Klyuchevskoy volcano (Kamchatka, Russia) can be predicted by our model when considering pressure changes of~10 7 Pa in a volume of~10 3-10 4 m 3 and realistic magma compositions. Our results show importance of the deep degassing in the generation of volcanic seismicity and suggest that the DLP swarms beneath active volcanoes might be related to the pulses of volatile-rich basaltic magmas rising from the mantle
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Deep long period volcanic earthquakes generated by degassing of volatile-rich basaltic magmas
'Springer Science and Business Media LLC', 2020Co-Authors: Melnik O., Shapiro Nikolay M., Galina N., Bergal-kuvikas OlgaAbstract:Deep long-period (DLP) earthquakes observed beneath active volcanoes are sometimes considered as precursors to eruptions. Their origin remains, however, unclear. Here, we present a possible DLP Generating Mechanism related to the rapid growth of gas bubbles in response to the slow decompression of over-saturated magma. For certain values of the gas and bubble content, the elastic deformation of surrounding rocks forced by the expanding bubbly magma can be fast enough to generate seismic waves. We show that amplitudes and frequencies of DLP earthquakes observed beneath the Klyuchevskoy volcano (Kamchatka, Russia) can be predicted by our model when considering pressure changes of ~107 Pa in a volume of ~103–104 m3 and realistic magma compositions. Our results show importance of the deep degassing in the generation of volcanic seismicity and suggest that the DLP swarms beneath active volcanoes might be related to the pulses of volatile-rich basaltic magmas rising from the mantle
M Norouzi - One of the best experts on this subject based on the ideXlab platform.
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on the comparative optimal analysis and synthesis of four bar function Generating Mechanism using different heuristic methods
Meccanica, 2013Co-Authors: S H Mirmahdi, M NorouziAbstract:In this research, optimal synthesis of function generation of four-bar linkages is investigated using different heuristic optimization methods. The novelty of this study is that we considered the five precision point’s distribution and both stroke angles of the follower and crank links as the optimization variables. Therefore, a non-linear optimization was done with seven variables. Different optimization techniques, including heuristic and gradient based methods were used for optimization and were completely compared. Finally, general solutions were found and distribution of precision points for some desired functions was rationalized. GA-Hybrid seems to be the best method in finding global optimums in cases that the problem is sorely nonlinear, and also it is fast. Even it seems that distribution of precision points is independent of stroke angles of the follower and crank links. Some precision points are out of the design domain, and they are sorted in a way that they can describe the behavior of desired function better.
Christian Hilty - One of the best experts on this subject based on the ideXlab platform.
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in situ determination of tacticity deactivation and kinetics in rac c2h4 1 indenyl 2 zrme b c6f5 4 and cp2zrme b c6f5 4 catalyzed polymerization of 1 hexene using 13c hyperpolarized nmr
Journal of the American Chemical Society, 2015Co-Authors: Chiahsiu Chen, Weichun Shih, Christian HiltyAbstract:The stereochemistry, kinetics, and Mechanism of olefin polymerization catalyzed by a set of zirconium-based metallocenes was studied by NMR using dissolution dynamic nuclear polarization (DNP). Hyperpolarized 1-hexene was polymerized in situ with a C2 symmetric catalyst, [(EBI)ZrMe][B(C6F5)4] (EBI = rac-(C2H4(1-indenyl)2)), and a C2v symmetric catalyst, [(Cp)2ZrMe][B(C6F5)4] (Cp = cyclopentadienyl). Hyperpolarized 13C NMR spectra were used to characterize product tacticity following initiation of the reaction. At the same time, a signal gain of 3 orders of magnitude from 13C hyperpolarization enabled the real time observation of catalyst-polymeryl species and deactivation products, such as vinylidene and a Zr-allyl complex. The compounds appearing in the reaction provide evidence for the existence of β-hydride elimination and formation of a dormant site via a methane-Generating Mechanism. The presence of a deactivating Mechanism was incorporated in a model used to determine kinetic parameters of the react...
