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APPROXIMATING OF POLYHEDRON OF NON-CONVEX SETS WITH NEURAL-BASED NETWORKS

Annotation

This article presents a method of constructing an approximating polyhedron of arbitrary non-convex multidimensional set with neural-based networks. An algorithm for constructing a neural network for solving this problem, as well as methods to simplify the structure of the neural network built to facilitate construction of the approximating polyhedron. Set out the distinctive features of the approach.

Keywords

approximation; neural networks; non-convex sets.

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UDC

514.11

Pages

931-932

References

1. Burmistrova L.V. Analiz i ispol'zovanie adaptivnykh metodov approksimatsii vypuklykh tel mnogogrannikami: avtoref. dis. ... kand. fiz.-mat. nauk / MGU im. M.V. Lomonosova. M., 2000. 2. Bronshteyn E.M. Approksimatsiya vypuklykh mnozhestv mnogogran-nikami // Sovremennaya matematika. Fundamental'nye napravle-niya. M., 2007. T. 22. 3. Berezkin V.E., Kamenev G.K., Lotov A.V. Realizatsiya metoda dos-tizhimykh tseley dlya nelineynykh modeley v MS Excel // Vychisli-tel'nyy tsentr Rossiyskoy akademii nauk. M., 1999. 4. Uossermen F. Neyrokomp'yuternaya tekhnika: teoriya i praktika. M., 1992. 5. Bronshteyn E.M., Ivanov L.D. O priblizhenii vypuklykh mnozhestv mnogogrannikami // Sibirskiy matematicheskiy zhurnal. 1975. T. 16. № 5. S. 1110-1112.

Received

26.05.2014

Section of issue

Scientific articles

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