DocumentCode
45595
Title
Reduction of space complexity based on symmetric TMVP
Author
Chunsheng Yang ; Jeng-Shyang Pan ; Chiou-Yng Lee ; Lijun Yan
Author_Institution
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen, China
Volume
51
Issue
9
fYear
2015
fDate
4 30 2015
Firstpage
697
Lastpage
699
Abstract
Toeplitz matrix-vector product (TMVP) decomposition is one of the high-precision multiplication algorithms. A symmetric TMVP (STMVP) decomposition is presented and theoretical analysis shows that the space complexity of the proposed STMVP scheme is less compared with the traditional TMVP approach. Gaussian normal basis (GNB) multiplication based on the proposed architecture can be used to reduce the space complexity.
Keywords
Toeplitz matrices; computational complexity; matrix decomposition; vectors; GNB multiplication; Gaussian normal basis multiplication; high-precision multiplication algorithms; space complexity reduction; symmetric TMVP decomposition; symmetric Toeplitz matrix-vector product decomposition;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el.2015.0014
Filename
7095707
Link To Document