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Approximation method for a fractional order transfer function with zero and pole
Archives of Control Sciences, 2014 The paper presents an approximation method for elementary fractional order transfer function containing both pole and zero. This class of transfer functions can be applied for example to build model - based special control algorithms. The proposed method
Oprzędkiewicz Krzysztof
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Dual Taylor Series, Spline Based Function and Integral Approximation and Applications
Mathematical and Computational Applications, 2019 In this paper, function approximation is utilized to establish functional series approximations to integrals. The starting point is the definition of a dual Taylor series, which is a natural extension of a Taylor series, and spline based series ...
Roy M. Howard
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Optimal Centers’ Allocation in Smoothing or Interpolating with Radial Basis Functions
Mathematics, 2021 Function interpolation and approximation are classical problems of vital importance in many science/engineering areas and communities. In this paper, we propose a powerful methodology for the optimal placement of centers, when approximating or ...
Pedro González-Rodelas +3 more
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Approximate Implicitization Using Linear Algebra
Journal of Applied Mathematics, 2012 We consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore well suited to floating-point ...
Oliver J. D. Barrowclough, Tor Dokken
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Quantum and classical algorithms for approximate submodular function minimization [PDF]
Quantum Information and Computation, 2019 Submodular functions are set functions mapping every subset of some ground set of size n into the real numbers and satisfying the diminishing returns property. Submodular minimization is an important field in discrete optimization theory due to its relevance for various branches of mathematics, computer science and economics.
Yassine Hamoudi +3 more
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Hardness of submodular cost allocation : lattice matching and a simplex coloring conjecture [PDF]
, 2014 We consider the Minimum Submodular Cost Allocation (MSCA) problem. In this problem, we are given k submodular cost functions f1, ... , fk: 2V -> R+ and the goal is to partition V into k sets A1, ..., Ak so as to minimize the total cost sumi = 1,k fi(Ai).
Vondrák, Jan, Ene, Alina
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IEEE Access, 2018 Reinforcement learning (RL) is an important machine learning paradigm that can be used for learning from the data obtained by the human-computer interface and the interaction in human-centered smart systems. One of the essential problems in RL algorithms
Dazi Li +3 more
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A sample decreasing threshold greedy-based algorithm for big data summarisation
Journal of Big Data, 2021 As the scale of datasets used for big data applications expands rapidly, there have been increased efforts to develop faster algorithms. This paper addresses big data summarisation problems using the submodular maximisation approach and proposes an ...
Teng Li +2 more
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Efficient by Precision Algorithms for Approximating Functions from Some Classes by Fourier Series
Кібернетика та комп'ютерні технологіїIntroduction. The problem of approximation can be considered as the basis of computational methods, namely, the approximation of individual functions or classes of functions by functions that are in some sense simpler than the functions being ...
Olena Kolomys
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Machines, 2021 In this paper, we consider the problem of selecting the most efficient optimization algorithm for neural network approximation—solving optimal control problems with mixed constraints.
Irina Bolodurina, Lyubov Zabrodina
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