Fast Implementation for the Singular Value and Eigenvalue Decomposition Based on FPGA. Issue 1 (1st January 2017)

• Record Type: Journal Article
• Authors: Zhang, Shuiping; Tian, Xin; Xiong, Chengyi; Tian, Jinwen; Ming, Delie
• Is Part Of: Chinese journal of electronics. Volume 26:Issue 1(2017)
• Page Start: 132
• Page End: 136
• Publication Date: 2017-01-01
• Subjects: SVD -- EVD -- Jacobi -- CORDIC -- FPGA; computational complexity -- digital arithmetic -- eigenvalues and eigenfunctions -- field programmable gate arrays -- singular value decomposition -- systolic arrays; eigenvalue decomposition -- singular value decomposition -- FPGA -- EVD -- SVD -- computational complexity -- sequential computation -- parallel computation -- simplified coordinate rotation digital computer -- CORDIC‐like algorithm -- filed‐programmable gate arrays -- systolic array; Electronics -- Periodicals; Electronics -- China -- Periodicals; Electronics; China; Periodicals; 621.38105
• DOI: 10.1049/cje.2016.06.033
• Languages: English
• ISSNs: 1022-4653

Abstract

Abstract : A fast and efficient hardware implementation for computing the Singular value decomposition (SVD) and Eigenvalue decomposition (EVD) is presented. Considering that the SVD and EVD are complex and expensive operations, to achieve high performance with low computing complexity, our approach takes full advantage of the combination of parallel and sequential computation, which can increase efficiently the hardware utilization. Besides, regarding to EVD, we propose a hardware solution of a simplified Coordinate rotation digital computer (CORDIC)‐like algorithm which can obtain higher speed. The performance analysis and comparison results show that the proposed methods can be realized on Filed‐programmable gate arrays (FPGAs) with less computation time by using systolic array. It will be shown that the proposed implementation could be an efficient alternative for real‐time applications.