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On the Best Exponent in Markov Inequality [PDF]
Potential Analysis, 2012 Recall that a compact set \(E\subset\mathbb{C}^{N}\) is said to be a Markov set if there are two constants \(M>0\) and \(m>0\) such that the following inequality \[ \||\nabla P|\|\leq M(\deg P)^m\| P\|_E,\tag{(*)} \] for each polynomial \(P\) holds, where \(\nabla P=(\frac{\partial P}{\partial z_1},\dotsc, \frac{\partial P}{\partial z_N})\), \(|\nabla ...
Baran, Mirosław +2 more
exaly +3 more sources
Approximation of the Constant in a Markov-Type Inequality on a Simplex Using Meta-Heuristics
Mathematics, 2021 Markov-type inequalities are often used in numerical solutions of differential equations, and their constants improve error bounds. In this paper, the upper approximation of the constant in a Markov-type inequality on a simplex is considered.
Grzegorz Sroka, Mariusz Oszust
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Transportation inequalities for Markov kernels and their applications [PDF]
Electronic Journal of Probability, 2021 38 pages.
Baudoin, Fabrice, Eldredge, Nathaniel
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Several Different Types of Convergence for ND Random Variables under Sublinear Expectations
Discrete Dynamics in Nature and Society, 2021 The goal of this paper is to build average convergence and almost sure convergence for ND (negatively dependent) sequences of random variables under sublinear expectation space.
Ziwei Liang, Qunying Wu
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An extremal inequality for long Markov chains [PDF]
2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2014 18 pages, 1 figure.
Thomas A. Courtade, Jiantao Jiao
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A General Solution for the Errors in Variables (EIV) Model with Equality and Inequality Constraints
Applied Sciences, 2022 Targeting the adjustment of the errors-in-variables (EIV) model with equality and inequality constraints, a general solution that is similar to the classical least square adjustment is proposed based on the penalty function and the weight in measurement.
Dengshan Huang, Yulin Tang, Qisheng Wang
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Exponential inequalities for nonstationary Markov chains [PDF]
Dependence Modeling, 2019 Abstract Exponential inequalities are main tools in machine learning theory. To prove exponential inequalities for non i.i.d random variables allows to extend many learning techniques to these variables. Indeed, much work has been done both on inequalities and learning theory for time series, in the past 15 years.
Alquier Pierre +2 more
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Finite-time energy-to-peak control for Markov jump systems with pure time delays
Measurement + Control, 2022 This study investigates finite-time energy-to-peak control for pure-time-delay Markov jump systems. The main objective is to obtain some theorems such that the corresponding pure-time-delay Markov jump systems are finite time energy-to-peak stable or ...
Falu Weng +4 more
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Schur-Type Inequalities for Complex Polynomials with no Zeros in the Unit Disk
Journal of Inequalities and Applications, 2007 Starting out from a question posed by T. Erdélyi and J. Szabados, we consider Schur-type inequalities for the classes of complex algebraic polynomials having no zeros within the unit disk D.
Szilárd Gy. Révész
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Discrete Dynamics in Nature and Society, 2020 Stochastic Lotka–Volterra model driven by small α-stable noises is used to describe population dynamics perturbed by random environment. However, parameters in the model are always unknown.
Chao Wei, Yan Wei, Yingying Zhou
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