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Approximation by Filter Functions [PDF]
, 2018 In this exploratory article, we draw attention to the common formal ground among various estimators such as the belief functions of evidence theory and their relatives, approximation quality of rough set theory, and contextual probability. The unifying concept will be a general filter function composed of a basic probability and a weighting which ...
Ivo Düntsch +2 more
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A Comparison between Fixed-Basis and Variable-Basis Schemes for Function Approximation and Functional Optimization [PDF]
, 2012 Fixed-basis and variable-basis approximation schemes are compared for the problems of function approximation and functional optimization (also known as infinite programming).
Gnecco, Giorgio +3 more
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Comparing policy gradient and value function based reinforcement learning methods in simulated electrical power trade [PDF]
, 2012 In electrical power engineering, reinforcement learning algorithms can be used to model the strategies of electricity market participants. However, traditional value function based reinforcement learning algorithms suffer from convergence issues when ...
Burt, Graeme +7 more
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Linear and Quadratic Interpolators Using Truncated-Matrix Multipliers and Squarers
Computers, 2015 This paper presents a technique for designing linear and quadratic interpolators for function approximation using truncated multipliers and squarers. Initial coefficient values are found using a Chebyshev-series approximation and then adjusted through ...
E. George Walters III
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Automatic Convexity Deduction for Efficient Function’s Range Bounding
Mathematics, 2021 Reliable bounding of a function’s range is essential for deterministic global optimization, approximation, locating roots of nonlinear equations, and several other computational mathematics areas.
Mikhail Posypkin, Oleg Khamisov
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Uniform Approximation of Functions with Discrete Approximation Functionals
Journal of Approximation Theory, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chandler, Colston, Gibson, Archie G.
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Approximation of binomial probability function for a normal probability function
, 2011 Notions of statistics and probabilityThe digital animation presents the approximation of the function of the binomial probability for a function of normal probability, also known as Gaussian distribution.
Rojo, Isabel Martín +3 more
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Frontiers in Energy Research, 2021 Solving the energy crisis and environmental pollution requires large-scale access to distributed energy and the popularization of electric vehicles.
Yuchen Liu +5 more
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Approximation of rough functions
Journal of Approximation Theory, 2016 16 pages, 3 ...
Michael F. Barnsley +3 more
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Approximations to Kelvin Functions [PDF]
Mathematics of Computation, 1963 While preparing a digital computer program to examine the behavior of largetaper hub flanges, it was found necessary to use approximations to the Kelvin functions ber x, bei x, ker x, and kei x, and to their first derivatives. To obtain full machine accuracy, the approximations were required to be correct to nine significant figures.
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