19 resultados para GW approximation
em Bulgarian Digital Mathematics Library at IMI-BAS
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Very often the experimental data are the realization of the process, fully determined by some unknown function, being distorted by hindrances. Treatment and experimental data analysis are substantially facilitated, if these data to represent as analytical expression. The experimental data processing algorithm and the example of using this algorithm for spectrographic analysis of oncologic preparations of blood is represented in this article.
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This paper is sponsored by the Ministry of Education and Research of the Republic of Bulgaria in the framework of project No 105 “Multimedia Packet Switching Networks Planning with Quality of Service and Traffic Management”.
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*This research was supported by the National Science Foundation Grant DMS 0200187 and by ONR Grant N00014-96-1-1003
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* Part of this work was done while the second author was on a visit at Tel Aviv University in March 2001
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* This work has been supported by the Office of Naval Research Contract Nr. N0014-91-J1343, the Army Research Office Contract Nr. DAAD 19-02-1-0028, the National Science Foundation grants DMS-0221642 and DMS-0200665, the Deutsche Forschungsgemeinschaft grant SFB 401, the IHP Network “Breaking Complexity” funded by the European Commission and the Alexan- der von Humboldt Foundation.
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Various combinatorial problems are effectively modelled in terms of (0,1) matrices. Origins are coming from n-cube geometry, hypergraph theory, inverse tomography problems, or directly from different models of application problems. Basically these problems are NP-complete. The paper considers a set of such problems and introduces approximation algorithms for their solutions applying Lagragean relaxation and related set of techniques.
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2000 Mathematics Subject Classification: 26A33 (primary), 35S15 (secondary)
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2000 Mathematics Subject Classification: 26A33 (primary), 35S15
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2000 Mathematics Subject Classification: 46B03
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2010 Mathematics Subject Classification: 41A25, 41A10.
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ACM Computing Classification System (1998): G.1.2.
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The deviations of some entire functions of exponential type from real-valued functions and their derivatives are estimated. As approximation metrics we use the Lp-norms and power variations on R. Theorems presented here correspond to the Ganelius and Popov results concerning the one-sided trigonometric approximation of periodic functions (see [4, 5 and 8]). Some related facts were announced in [2, 3, 6 and 7].
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We introduce a modification of the familiar cut function by replacing the linear part in its definition by a polynomial of degree p + 1 obtaining thus a sigmoid function called generalized cut function of degree p + 1 (GCFP). We then study the uniform approximation of the (GCFP) by smooth sigmoid functions such as the logistic and the shifted logistic functions. The limiting case of the interval-valued Heaviside step function is also discussed which imposes the use of Hausdorff metric. Numerical examples are presented using CAS MATHEMATICA.
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AMS Subject Classification 2010: 41A25, 41A35, 41A40, 41A63, 41A65, 42A38, 42A85, 42B10, 42B20
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MSC 2010: 41A25, 41A35