DocumentCode :
3092567
Title :
Parallel computing of eigenvalue of doubly stochastic matrix
Author :
Dake, He ; Jianbo, Wang
Author_Institution :
Southwest Jiaotong Univ., Chengdu, China
fYear :
2002
fDate :
23-25 Oct. 2002
Firstpage :
355
Lastpage :
358
Abstract :
The transition probability matrix of the Markov cipher is doubly stochastic. The eigenvalue of the matrix with maximum magnitude less than one plays an important role in designing the Markov cipher. This paper provides a parallel algorithm for computing the eigenvalue of the doubly stochastic matrix A of size 65535/spl times/65535, which comes from a Markov cipher shrunken model with both 16 bit plaintext and ciphertext. An analysis of the complexity of the parallel algorithm is also considered.
Keywords :
Markov processes; computational complexity; eigenvalues and eigenfunctions; matrix algebra; parallel algorithms; 16 bit; Markov cipher; ciphertext; complexity; doubly stochastic transition probability matrix; eigenvalue; parallel algorithm; parallel computing; plaintext; Algorithm design and analysis; Concurrent computing; Eigenvalues and eigenfunctions; Helium; High performance computing; Parallel algorithms; Parallel processing; Performance analysis; Stochastic processes; Symmetric matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Algorithms and Architectures for Parallel Processing, 2002. Proceedings. Fifth International Conference on
Conference_Location :
Beijing, China
Print_ISBN :
0-7695-1512-6
Type :
conf
DOI :
10.1109/ICAPP.2002.1173601
Filename :
1173601
Link To Document :
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