IEEE Access | 卷:9 |
Sparse Matrix Based Low-Complexity, Recursive, and Radix-2 Algorithms for Discrete Sine Transforms | |
Levi E. Lingsch1  Sirani M. Perera2  | |
[1] Department of Aerospace Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL, USA; | |
[2] Department of Mathematics, Embry-Riddle Aeronautical University, Daytona Beach, FL, USA; | |
关键词: Discrete sine transforms; self/completely recursive and radix-2 algorithms; complexity and performance of algorithms; sparse and orthogonal matrices; signal flow graphs; | |
DOI : 10.1109/ACCESS.2021.3120051 | |
来源: DOAJ |
【 摘 要 】
This paper presents factorizations of each discrete sine transform (DST) matrix of types I, II, III, and IV into a product of sparse, diagonal, bidiagonal, and scaled orthogonal matrices. Based on the proposed matrix factorization formulas, reduced multiplication complexity, recursive, and radix-2 DST I-IV algorithms are presented. We will present the lowest multiplication complexity DST-IV algorithm in the literature. The paper fills a gap in the self-recursive, exact, and radix-2 DST I-IIII algorithms executed via diagonal, bidiagonal, scaled orthogonal, and simple matrix factors for any input
【 授权许可】
Unknown