Results 271 to 280 of about 7,666,446 (331)
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General Relativity and Gravitation, 1977
We show how, for a wide class of asymptotically flat space-times, it is possible to solve the equation for asymptotically shear-free complex null cones (the good-cut equation) to first approximation, and thereby obtain first-order ℋ spaces and associated firstorder asymptotic projective twistor spaces.
E. T. Newman, K. P. Tod
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We show how, for a wide class of asymptotically flat space-times, it is possible to solve the equation for asymptotically shear-free complex null cones (the good-cut equation) to first approximation, and thereby obtain first-order ℋ spaces and associated firstorder asymptotic projective twistor spaces.
E. T. Newman, K. P. Tod
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Soft Nearness Approximation Spaces
Fundamenta Informaticae, 2013In 1999, Molodtsov introduced the theory of soft sets, which can be seen as a new mathematical approach to vagueness. In 2002, near set theory was initiated by J. F. Peters as a generalization of Pawlak's rough set theory. In the near set approach, every perceptual granule is a set of objects that have their origin in the physical world.
Öztürk, Mehmet Ali, Ịnan, Ebubekir
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Three-way Decisions with Rough Membership Functions in Covering Approximation Space
Fundamenta Informaticae, 2019Rough membership functions in covering approximation space not only give numerical characterizations of covering-based rough set approximations, but also establish the relationship between covering-based rough sets and fuzzy covering-based rough sets. In
Bingqiao Yang, B. Hu, Junsheng Qiao
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Lipschitz approximable Banach spaces
Commentationes Mathematicae Universitatis Carolinae, 2020It is shown that a separable Banach space with the bounded compact approximation property is Lipschitz-approximable. Using known examples one deduces that there is a Lipschitz-approximable reflexive separable Banach space which fails the approximation property.
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Space-Bounded Query Approximation
2015When dealing with large amounts of data, exact query answering is not always feasible. We propose a query approximation method that, given an upper bound on the amount of data that can be used (i.e., for which query evaluation is still feasible), identifies a part C of the data D that (i) fits in the available space budget; and (ii) provides accurate ...
Cule, Boris +2 more
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Fuzzy β-covering approximation spaces
International Journal of Approximate Reasoning, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Xiaohong, Wang, Jingqian
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Constrained Approximation in Sobolev Spaces
Canadian Journal of Mathematics, 1997AbstractPositive, copositive, onesided and intertwining (co-onesided) polynomial and spline approximations of functions are considered. Both uniform and pointwise estimates, which are exact in some sense, are obtained.
Hu, Y. K., Kopotun, K. A., Yu, X. M.
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The Product Approximation Spaces of Two Covering Approximation Spaces
2016 8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2016In this paper, we define a new type of covering approximation space which is called product approximation space of two covering approximation spaces. Based on the important concepts of neighborhood and complementary neighborhood in covering rough set theory, we define four pairs of lower and upper approximation operators on this type of approximation ...
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Information quanta and approximation spaces II: generalised approximation spaces
2005 IEEE International Conference on Granular Computing, 2005In the first part we have introduced non-classical upper and lower approximations of subsets of objects or properties, on the basis of the properties featured by Galois adjunctions between intensional and extensionnal operators. In the present part we introduce the higher order notions of an "information quantum" an "information quantum relational ...
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Weak Dependencies in Approximation Spaces
Fundamenta Informaticae, 2013The article reviews the basics of the variable precision rough set and the Bayesian approaches to data dependencies detection and analysis. The variable precision rough set and the Bayesian rough set theories are extensions of the rough set theory. They are focused on the recognition and modelling of set overlap-based, also referred to as probabilistic,
Ziarko, Wojciech, Chen, Xugunag
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