Art

J-GLOBAL ID：202002227292917157   Reference number：20A2355859

Predicting the convergence of BiCG method from grayscale matrix images

グレースケール行列画像からのBiCG法の収束の予測

Author (2)： Ota Ryo (Graduate School of Library, Information and Media Studies, University of Tsukuba) ,  Hasegawa Hidehiko (Faculty of Library, Information and Media Science, University of Tsukuba)
Material： JSIAM Letters (Web)  (JSIAM Lett (Web))
Volume： 12  Page： 45-48(J-STAGE)  Publication year： 2020 
JST Material Number： U0115A  ISSN： 1883-0617  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： *gray scale ,  *conjugate gradient method ,  *image processing system ,  convergence ,  prediction technique ,  *neural network (biomodel) ,  matrix (mathematics) ,  cross validation method ,  Data Collection ,  evaluation test ,  *convolutional neuralnetwork ,  *measuring instrument ,  Mathematics ,  theory of errors
Semi thesaurus term： 非対称行列

Author keywords (3)： pattern recognition ,  classification of matrices ,  iterative methods

JST classification (4)： Measuring instruments in general  (AD02000X) ,  Graphic and image processing in general  (JE04010I) ,  Numerical computation  (JE02000J) ,  Neurocomputers  (JC06010Q)

Reference (8)：

• 1) R. Barrett et al., Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods, SIAM, Philadelphia, 1994.
• 2) A. Krizhevsky, I. Sutskever and G. E. Hinton G. E. Hinton, ImageNet classification with deep convolutional neural networks, in: Proc. of the 25th International Conference on Neural Information Processing Systems, pp. 1097-1105, 2012.
• 3) M. Götz and H. Anzt, Machine learning-aided numerical linear algebra: convolutional neural networks for the efficient preconditioner generation, in: 2018 IEEE/ACM 9th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (scalA), pp. 49-56, 2018.
• 4) K. Yamada et al., Preconditioner auto-tuning using deep learning for sparse iterative algorithms, in: 2018 Sixth International Symposium on Computing and Networking Workshops (CANDARW), pp. 257-262, 2018.
• 5) T. A. Davis, Y. Hu and S. Kolodziej, The SuiteSparse Matrix Collection, https://sparse.tamu.edu.

Terms in the title (4)： グレースケール ,  行列 ,  収束 ,  予測