Researching methods of reconstruction of threedimensional crystal lattice from images of projections

Shirokanev, A. S.; Kirsh, Dmitriy; Kupriyanov, Alexander

doi:10.18287/1613-0073-2015-1490-290-297

Cited by 4 publications

(3 citation statements)

References 7 publications

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“…Методика обучения Для обучения нейронных сетей были использованы данные о сгенерированных элементарных ячейках кристаллических решёток 7 различных типов. Генерация проводилась с использованием системы моделирования кристаллических решёток, описанной в работах [22,23], при следующих условиях:…”

Section: рис 4 структура нейронной нечёткой продукционной сети мамдunclassified

Application of fuzzy neural networks for defining crystal lattice types in nanoscale images

Солдатова¹,

Lyozina²,

Kupriyanov³

et al. 2015

Computer Optics

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The article proposes the application of neural fuzzy networks for defining the overlapping classes of crystal lattices. We discuss the following neural fuzzy networks: Takagi-Sugeno-Kung network and a modification of Wang-Mendel neural fuzzy network proposed by the authors. A three-step scheme of neural network training is proposed. The results prove the efficiency of the proposed approach for the determination of crystal lattice types.

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Section: рис 4 структура нейронной нечёткой продукционной сети мамдunclassified

Application of fuzzy neural networks for defining crystal lattice types in nanoscale images

Солдатова¹,

Lyozina²,

Kupriyanov³

et al. 2015

Computer Optics

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“…Structural identification of crystal lattices in three-dimensional space is one of the basic problems of X-ray diffraction analysis [1]. The main difficulties are the reconstruction of three-dimensional objects [2,3] and the ambiguity of unit cell choice from which the ambiguity of lattice system identification arises [4,5]. To solve the problem of structural identification in three dimensional space, we proposed two approaches: the first was based on parametric identification methods [6] and the second was based on application of fuzzy neural networks [7].…”

Section: Introductionmentioning

confidence: 99%

Parallel Implementations of Parametric Identification Algorithms for Threedimensional Crystal Lattices

Kirsh

Kupriyanov

2016

Collection of Selected Papers of the II International Conference on Information Technology and Nanotechnology

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The article describes parallel implementations of two parametric identification algorithms. The first algorithm is based on the estimation of Bravais unit cell parameters, and the second one estimates Wigner-Seitz cell volumes. The developed parallel implementations are based on the two-tier model of concurrency. An external tier of concurrency uses Message Passing Interface (MPI) technique to distribute parametric identification tasks between computing nodes. An internal tier uses Open Multi-Processing (OpenMP) technique to split single steps of the parametric identification algorithms into independent subtasks. Experimental results on multi-processor / multi-core systems have demonstrated almost linear speedup of the parallel implementations, confirmed the effectiveness of the two-tier concurrency model and proved the stability of the identification approach under lattice distortion.Citation: Kirsh D, Kupriyanov A. Parallel implementations of parametric identification algorithms for three-dimensional crystal lattices. High-Performance ComputingKirsh DV, Kupriyanov AV… Information Technology and Nanotechnology (ITNT-2016) 452

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“…In particular in crystallography, reconstruction of a three-dimensional crystal lattice structure is related directly to a parameter identification problem, which is one of the basic problems of X-ray diffraction analysis [4,5]. Unfortunately, such methods either lack sufficient accuracy or fail to describe comprehensively the crystal properties [4,[6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Application of Gradient Steepest Descent Method to the Problem of Crystal Lattice Parametric Identification

Shirokanev

Kirsh

Kupriyanov

et al. 2016

Collection of Selected Papers of the II International Conference on Information Technology and Nanotechnology

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Abstract. The objective of this paperwork is the development of a crystal lattice parameter identification algorithm, which allows obtaining a more accurate solution compared to the Bravais unit cell estimation algorithm. To achieve the objective, we suggest solving the parameter identification problem using the steepest descent gradient method. The study of the parameter identification accuracy was conducted on a large number of modeled crystal lattices using the edges and angles similarity measures for Bravais unit cells.Keywords: crystal lattice, Bravais unit cell, Wigner-Seitz unit cell, similarity measure, translation vector, parameter identification, gradient steepest descent method.Citation: Shirokanev AS, Kirsh DV, Kupriyanov AV. Application of gradient steepest descent method to the problem of crystal lattice parametric identification.

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Researching methods of reconstruction of threedimensional crystal lattice from images of projections

Cited by 4 publications

References 7 publications

Application of fuzzy neural networks for defining crystal lattice types in nanoscale images

Application of fuzzy neural networks for defining crystal lattice types in nanoscale images

Parallel Implementations of Parametric Identification Algorithms for Threedimensional Crystal Lattices

Application of Gradient Steepest Descent Method to the Problem of Crystal Lattice Parametric Identification

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