Graph products with specified domains for configuration processing and formation of the adjacency matrices

2010 ◽  
Vol 27 (2) ◽  
pp. 205-224 ◽  
Author(s):  
A. Kaveh ◽  
B. Alinejad
2021 ◽  
Vol 20 (3) ◽  
Author(s):  
Sho Kubota ◽  
Etsuo Segawa ◽  
Tetsuji Taniguchi

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1522
Author(s):  
Anna Concas ◽  
Lothar Reichel ◽  
Giuseppe Rodriguez ◽  
Yunzi Zhang

The power method is commonly applied to compute the Perron vector of large adjacency matrices. Blondel et al. [SIAM Rev. 46, 2004] investigated its performance when the adjacency matrix has multiple eigenvalues of the same magnitude. It is well known that the Lanczos method typically requires fewer iterations than the power method to determine eigenvectors with the desired accuracy. However, the Lanczos method demands more computer storage, which may make it impractical to apply to very large problems. The present paper adapts the analysis by Blondel et al. to the Lanczos and restarted Lanczos methods. The restarted methods are found to yield fast convergence and to require less computer storage than the Lanczos method. Computed examples illustrate the theory presented. Applications of the Arnoldi method are also discussed.


2001 ◽  
Vol 325 (1-3) ◽  
pp. 191-207
Author(s):  
Wai-Shun Cheung ◽  
Chi-Kwong Li ◽  
D.D. Olesky ◽  
P. van den Driessche

2010 ◽  
Vol 55 (2-3) ◽  
pp. 221-233 ◽  
Author(s):  
M. Abreu ◽  
C. Balbuena ◽  
D. Labbate

2009 ◽  
Vol 30 (5) ◽  
pp. 1048-1053 ◽  
Author(s):  
Kannan Balakrishnan ◽  
Manoj Changat ◽  
Iztok Peterin ◽  
Simon Špacapan ◽  
Primož Šparl ◽  
...  

2017 ◽  
Vol 54 (1) ◽  
pp. 141-149
Author(s):  
S. Francis Raj ◽  
T. Kavaskar
Keyword(s):  

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