The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Harro Walk - One of the best experts on this subject based on the ideXlab platform.
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Estimation of the Essential Supremum of a regression function
Statistics & Probability Letters, 2011Co-Authors: Michael Köhler, Adam Krzyżak, Harro WalkAbstract:Given an independent and identically distributed sample of the distribution of an -valued random vector (X,Y), the problem of estimation of the Essential Supremum of the corresponding regression function is considered. Estimates are constructed, which converge almost surely to this value whenever the dependent variable Y satisfies some weak integrability condition.
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Estimation of the Essential Supremum of a regression function
Statistics & Probability Letters, 2011Co-Authors: Michael Köhler, Adam Krzyżak, Harro WalkAbstract:Abstract Given an independent and identically distributed sample of the distribution of an R d × R -valued random vector ( X , Y ) , the problem of estimation of the Essential Supremum of the corresponding regression function m ( x ) = E { Y | X = x } is considered. Estimates are constructed, which converge almost surely to this value whenever the dependent variable Y satisfies some weak integrability condition.
Michael Köhler - One of the best experts on this subject based on the ideXlab platform.
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Estimation of the Essential Supremum of a regression function
Statistics & Probability Letters, 2011Co-Authors: Michael Köhler, Adam Krzyżak, Harro WalkAbstract:Given an independent and identically distributed sample of the distribution of an -valued random vector (X,Y), the problem of estimation of the Essential Supremum of the corresponding regression function is considered. Estimates are constructed, which converge almost surely to this value whenever the dependent variable Y satisfies some weak integrability condition.
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Estimation of the Essential Supremum of a regression function
Statistics & Probability Letters, 2011Co-Authors: Michael Köhler, Adam Krzyżak, Harro WalkAbstract:Abstract Given an independent and identically distributed sample of the distribution of an R d × R -valued random vector ( X , Y ) , the problem of estimation of the Essential Supremum of the corresponding regression function m ( x ) = E { Y | X = x } is considered. Estimates are constructed, which converge almost surely to this value whenever the dependent variable Y satisfies some weak integrability condition.
Rodolphe Sepulchre - One of the best experts on this subject based on the ideXlab platform.
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The $\mathcal{H}_{\infty,p}$ norm as the differential $\mathcal{L}_{2,p}$ gain of a $p$-dominant system
arXiv: Optimization and Control, 2019Co-Authors: Alberto Padoan, Fulvio Forni, Rodolphe SepulchreAbstract:The differential $\mathcal{L}_{2,p}$ gain of a linear, time-invariant, $p$-dominant system is shown to coincide with the $\mathcal{H}_{\infty,p}$ norm of its transfer function $G$, defined as the Essential Supremum of the absolute value of $G$ over a vertical strip in the complex plane such that $p$ poles of $G$ lie to right of the strip. The close analogy between the $\mathcal{H}_{\infty,p}$ norm and the classical $\mathcal{H}_{\infty}$ norm suggests that robust dominance of linear systems can be studied along the same lines as robust stability. This property can be exploited in the analysis and design of nonlinear uncertain systems that can be decomposed as the feedback interconnection of a linear, time-invariant system with bounded gain uncertainties or nonlinearities.
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CDC - The H ∞,p norm as the differential L 2,p gain of a p-dominant system
2019 IEEE 58th Conference on Decision and Control (CDC), 2019Co-Authors: Alberto Padoan, Fulvio Forni, Rodolphe SepulchreAbstract:The differential ${\mathcal{L}_{2,p}}$ gain of a linear, time-invariant, p-dominant system is shown to coincide with the ${\mathcal{H}_{\infty ,p}}$ norm of its transfer function G, defined as the Essential Supremum of the absolute value of G over a vertical strip in the complex plane such that p poles of G lie to right of the strip. The close analogy between the ${\mathcal{H}_{\infty ,p}}$ norm and the classical ${\mathcal{H}_\infty }$ norm suggests that robust H dominance of linear systems can be studied along the same lines as robust stability. This property can be exploited in the analysis and design of nonlinear uncertain systems that can be decomposed as the feedback interconnection of a linear, time-invariant system with bounded gain uncertainties or nonlinearities.
Jaroslav Šupina - One of the best experts on this subject based on the ideXlab platform.
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Beyond the scope of super level measures
Fuzzy Sets and Systems, 2019Co-Authors: Lenka Halčinová, Ondrej Hutník, Jozef Kiseľák, Jaroslav ŠupinaAbstract:Abstract We expand the theoretical background of the recently introduced outer measure spaces theory of Do and Thiele in harmonic and time-frequency analysis context. In the context of non-additive measures and integrals, we propose a certain framework for a natural extension of the basic ingredients of the theory (i.e., the concept of size, outer Essential Supremum and the corresponding super level measure) which, besides the covering the previously considered cases, permits us to introduce a further substantial extension of a class of non-additive integrals. All these notions are studied in detail and exemplified.
Adam Krzyżak - One of the best experts on this subject based on the ideXlab platform.
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Estimation of the Essential Supremum of a regression function
Statistics & Probability Letters, 2011Co-Authors: Michael Köhler, Adam Krzyżak, Harro WalkAbstract:Given an independent and identically distributed sample of the distribution of an -valued random vector (X,Y), the problem of estimation of the Essential Supremum of the corresponding regression function is considered. Estimates are constructed, which converge almost surely to this value whenever the dependent variable Y satisfies some weak integrability condition.
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Estimation of the Essential Supremum of a regression function
Statistics & Probability Letters, 2011Co-Authors: Michael Köhler, Adam Krzyżak, Harro WalkAbstract:Abstract Given an independent and identically distributed sample of the distribution of an R d × R -valued random vector ( X , Y ) , the problem of estimation of the Essential Supremum of the corresponding regression function m ( x ) = E { Y | X = x } is considered. Estimates are constructed, which converge almost surely to this value whenever the dependent variable Y satisfies some weak integrability condition.