Integration of macromolecular diffraction data using radial basis function networks
Author(s) -
Pokrić Boris,
Allinson Nigel M.,
Helliwell John R.
Publication year - 2000
Publication title -
journal of synchrotron radiation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.172
H-Index - 99
ISSN - 1600-5775
DOI - 10.1107/s0909049500012929
Subject(s) - diffraction , radial basis function , basis (linear algebra) , function (biology) , computer science , optics , radial basis function network , algorithm , physics , artificial intelligence , mathematics , artificial neural network , geometry , evolutionary biology , biology
This paper presents a novel approach for intensity calculation of X‐ray diffraction spots based on a two‐stage radial basis function (RBF) network. The first stage uses pre‐determined reference profiles from a database as basis functions in order to locate the diffraction spots and identify any overlapping regions. The second‐stage RBF network employs narrow basis functions capable of local modifications of the reference profiles leading to a more accurate observed diffraction spot approximation and therefore accurate determination of spot positions and integrated intensities.
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