Results 41 to 50 of about 623,284 (221)

Minkowski’s Inequality Based Sensitivity Analysis of Fuzzy Signatures

open access: yesJournal of Artificial Intelligence and Soft Computing Research, 2016
Fuzzy signatures were introduced as special tools to describe and handle complex systems without their detailed mathematical models. The input parameters of these systems naturally have uncertainties, due to human activities or lack of precise data ...
I. Harmati, Á. Bukovics, L. Kóczy
semanticscholar   +1 more source

On Jensen’s inequality, Hölder’s inequality, and Minkowski’s inequality for dynamically consistent nonlinear evaluations

open access: yes, 2015
In this paper, the dynamically consistent nonlinear evaluations that were introduced by Peng are considered in probability space L2(Ω,F,(Ft)t≥0,P)$L^{2} (\Omega,{\mathcal{F}}, ({\mathcal {F}}_{t} )_{t\geq0},P )$.
Zhaojun Zong, F. Hu, C. Yin, Helin Wu
semanticscholar   +1 more source

The log-Brunn–Minkowski inequality

open access: yesAdvances in Mathematics, 2012
It is conjectured that for origin-symmetric convex bodies, there exist a family of inequalities each of which is stronger than the classical Minkowski mixed-volume inequality and a family of inequalities each of which is stronger than the classical Brunn-Minkowski inequality.
Böröczky, Károly (Ifj.)   +3 more
openaire   +3 more sources

The Orlicz Brunn–Minkowski inequality

open access: yesAdvances in Mathematics, 2014
The Orlicz-Brunn-Minkowski theory was introduced by Lutwak, Yang and Zhang, being an extension of the classical Brunn-Minkowski theory. It represents a generalization of the \(L_p\)-Brunn-Minkowski theory. For a convex, strictly increasing \(\phi:[0,\infty]\longrightarrow [0,\infty)\), with \(\phi(0)=0\) and \(K,L\) convex and compact sets containing ...
Xi, Dongmeng   +2 more
openaire   +2 more sources

Variable Ranges in Linear Constraints [PDF]

open access: yes, 2010
We introduce an extension of linear constraints, called linearrange constraints, which allows for (meta-)reasoning about the approximation width of variables. Semantics for linearrange constraints is provided in terms of parameterized linear systems.
Fred Mesnard, Salvatore Ruggieri
core   +2 more sources

Generalizations of Minkowski and Beckenbach–Dresher Inequalities and Functionals on Time Scales

open access: yesInternational Journal of Analysis and Applications, 2020
We generalize integral forms of the Minkowski inequality and Beckenbach–Dresher inequality on time scales. Also, we investigate a converse of Minkowski’s inequality and several functionals arising from the Minkowski inequality and the Beckenbach–Dresher ...
Rabia Bibi   +2 more
doaj  

Diamond-α Jensen's Inequality on Time Scales

open access: yesJournal of Inequalities and Applications, 2008
The theory and applications of dynamic derivatives on time scales have recently received considerable attention. The primary purpose of this paper is to give basic properties of diamond-α derivatives which are a linear combination of delta and nabla ...
Delfim F. M. Torres   +2 more
doaj   +1 more source

Ricci-flat Metrics with U(1) Action and the Dirichlet Boundary-value Problem in Riemannian Quantum Gravity and Isoperimetric Inequalities [PDF]

open access: yes, 2003
The Dirichlet boundary-value problem and isoperimetric inequalities for positive definite regular solutions of the vacuum Einstein equations are studied in arbitrary dimensions for the class of metrics with boundaries admitting a U(1) action.
Akbar M M   +29 more
core   +2 more sources

Non-uniqueness of weak solutions for the fractal Burgers equation [PDF]

open access: yes, 2009
The notion of Kruzhkov entropy solution was extended by the first author in 2007 to conservation laws with a fractional laplacian diffusion term; this notion led to well-posedness for the Cauchy problem in the $L^\infty$-framework.
Alibaud   +26 more
core   +5 more sources

Risk‐aware safe reinforcement learning for control of stochastic linear systems

open access: yesAsian Journal of Control, EarlyView.
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili   +2 more
wiley   +1 more source

Home - About - Disclaimer - Privacy