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Technological information extraction of free form surfaces using neural networksKorošec, Marjan, 1961-The aim of this paper is to show how to predict the accurate machining technology for the particular free form NURBS or B-spline surface. Since that kind of a surface is very hard to describe in an ... analytical manner, the topological and geometrical information about the surface was acquired with the help of self-organized neural networks (NNs) and first- or second-order statistic parameters. It is proved that the most significant parameter in thisprocess is the curvature, especially when rapid changes of curvature on a free form surface occurred. As the Gaussian distribution of surface curvaturesand slope gradient data were presumed, the mean and variance was used for one-dimensional data presentation, and the Hebbian output data vectorwas used to assess probability, density function and distribution of thepresented data. For collecting the maximum amount of surface information, the principal component analysis method inside the Hebbian NN was used.Vir: Neural computing & applications. - ISSN 0941-0643 (Letn. 16, št. 4/5, 2007, str. 453-463)Vrsta gradiva - e-članek ; neleposlovje za odrasleLeto - 2007Jezik - angleškiCOBISS.SI-ID - 9749275
Avtor
Korošec, Marjan, 1961-
Teme
nevronalne mreže |
obdelovalne tehnologije |
B-spline površine |
Gaussove porazdelitve |
anlizne metode |
verjetnostne funkcije |
analize variance |
proste oblike |
proste oblike |
neural network |
self-organized map |
probability density function |
variance |
free form surface |
shape distribution function
Vnos na polico
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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Korošec, Marjan, 1961- | 19048 |
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