Reduction of space complexity based on symmetric TMVP

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. G...

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Bibliographic Details
Published in:Electronics letters 2015-04, Vol.51 (9), p.697-699
Main Authors: Yang, Chunsheng, Pan, Jeng-Shyang, Lee, Chiou-Yng, Yan, Lijun
Format: Article
Language:English
Subjects:
Algorithms
Architecture
Complexity
computational complexity
Decomposition
Gaussian
Gaussian normal basis multiplication
GNB multiplication
high‐precision multiplication algorithms
Information and communications
matrix decomposition
Multiplication
Reduction
space complexity reduction
symmetric TMVP decomposition
symmetric Toeplitz matrix‐vector product decomposition
Symmetry
Toeplitz matrices
vectors
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Summary: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.
ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2015.0014