2014•IEEE Transactions on Signal ProcessingRequires access

Scaled Radix-2/8 Algorithm for Efficient Computation of Length-$N=2^{m}$ DFTs

Weihua Zheng, Kenli Li, Keqin Li

Open publisher page 21 citations

Abstract

This paper presents a scaled radix-2/8 fast Fourier transform (FFT) (SR28FFT) algorithm for computing length- N = 2mdiscrete Fourier transforms (DFTs) scaled by complex number rotating factors. The idea of the SR28FFT algorithm is from the modified split radix FFT (MSRFFT) algorithm, and its purpose is to furnish other algorithms with high efficiency but without shortcomings of the MSRFFT algorithm. A novel radix-2/4 FFT (NR24FFT) algorithm and a novel radix-2/8 FFT (NR28FFT) algorithm are proposed. These two algorithms use SR28FFT to calculate their sub-DFTs of odd-indexed terms. Several aspects of the two algorithms such as computational complexity, computation accuracy, and coefficient evaluations or accesses to the lookup table all are improved. The bit-reverse method can be used for their order permutation and no extra memory is required to store their extra coefficients by the two novel algorithms, which contribute significantly to the performance of the FFT algorithms. The SR28FFT algorithm can also be applied to other algorithms whose decomposition contains sub-DFTs of powers-of-two. The Appendix presents an algorithm named SR28FFT-2 for further reducing the number of arithmetic operations, and NR24FFT and NR28FFT algorithms based on SR28FFT-2 requires fewer real operations than that required by the MSRFFT algorithm.

About this research paper

What this paper is about

This paper presents a scaled radix-2/8 fast Fourier transform (FFT) (SR28FFT) algorithm for computing length- N = 2mdiscrete Fourier transforms (DFTs) scaled by complex number rotating factors. The idea of the SR28FFT algorithm is from the modified split radix FFT (MSRFFT) algorithm, and its purpose is to furnish other algorithms with high efficiency but without shortcomings of the MSRFFT algorithm. A novel radix-2/4 FFT (NR24FFT) algorithm and a novel radix-2/8 FFT (NR28FFT) algorithm are proposed. These two algorithms use SR28FFT to calculate their sub-DFTs of odd-indexed terms. Several aspects of the two algorithms such as computational complexity, computation accuracy, and coefficient evaluations or accesses to the lookup table all are improved. The bit-reverse method can be used for their order permutation and no extra memory is required to store their extra coefficients by the two novel algorithms, which contribute significantly to the performance of the FFT algorithms. The SR28FFT algorithm can also be applied to other algorithms whose decomposition contains sub-DFTs of powers-of-two. The Appendix presents an algorithm named SR28FFT-2 for further reducing the number of arithmetic operations, and NR24FFT and NR28FFT algorithms based on SR28FFT-2 requires fewer real operations than that required by the MSRFFT algorithm.

Why it matters

OpenAlex reports 21 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

This paper presents a scaled radix-2/8 fast Fourier transform (FFT) (SR28FFT) algorithm for computing length- N = 2mdiscrete Fourier transforms (DFTs) scaled by complex number rotating factors. The idea of the SR28FFT algorithm is from the modified split radix FFT (MSRFFT) algorithm, and its purpose is to furnish other algorithms with high efficiency but without shortcomings of the MSRFFT algorithm. A novel radix-2/4 FFT (NR24FFT) algorithm and a novel radix-2/8 FFT (NR28FFT) algorithm are proposed. These two algorithms use SR28FFT to calculate their sub-DFTs of odd-indexed terms. Several aspects of the two algorithms such as computational complexity, computation accuracy, and coefficient evaluations or accesses to the lookup table all are improved. The bit-reverse method can be used for their order permutation and no extra memory is required to store their extra coefficients by the two novel algorithms, which contribute significantly to the performance of the FFT algorithms. The SR28FFT algorithm can also be applied to other algorithms whose decomposition contains sub-DFTs of powers-of-two. The Appendix presents an algorithm named SR28FFT-2 for further reducing the number of arithmetic operations, and NR24FFT and NR28FFT algorithms based on SR28FFT-2 requires fewer real operations than that required by the MSRFFT algorithm.

Key concepts: Split-radix FFT algorithm, Fast Fourier transform, Algorithm, Prime-factor FFT algorithm, Twiddle factor, Computer science, Lookup table, Computation

Related papers

Back to paper searchBrowse research topicsOriginal source
Scaled Radix-2/8 Algorithm for Efficient Computation of Length-$N=2^{m}$ DFTs — Research Paper | ScholarLens