
Proceedings Paper
Hardware efficient implementation of DFT using an improved first-order moments based cyclic convolution structureFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
This paper presents hardware efficient designs for implementing the one-dimensional (1D) discrete Fourier transform (DFT). Once DFT is formulated as the cyclic convolution form, the improved first-order moments-based cyclic convolution structure can be used as the basic computing unit for the DFT computation, which only contains a control module, a barrel shifter and (N-1)/2 accumulation units. After decomposing and reordering the twiddle factors, all that remains to do is shifting the input data sequence and accumulating them under the control of the statistical results on the twiddle factors. The whole calculation process only contains shift operations and additions with no need for multipliers and large memory. Compared with the previous first-order moments-based structure for DFT, the proposed designs have the advantages of less hardware consumption, lower power consumption and the flexibility to achieve better performance in certain cases. A series of experiments have proven the high performance of the proposed designs in terms of the area time product and power consumption. Similar efficient designs can be obtained for other computations, such as DCT/IDCT, DST/IDST, digital filter and correlation by transforming them into the forms of the first-order moments based cyclic convolution.
Paper Details
Date Published: 14 December 2015
PDF: 8 pages
Proc. SPIE 9814, MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing, 981407 (14 December 2015); doi: 10.1117/12.2205718
Published in SPIE Proceedings Vol. 9814:
MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing
Jianguo Liu, Editor(s)
PDF: 8 pages
Proc. SPIE 9814, MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing, 981407 (14 December 2015); doi: 10.1117/12.2205718
Show Author Affiliations
Published in SPIE Proceedings Vol. 9814:
MIPPR 2015: Parallel Processing of Images and Optimization; and Medical Imaging Processing
Jianguo Liu, Editor(s)
© SPIE. Terms of Use
