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Split-radix FFT algorithm
About: Split-radix FFT algorithm is a research topic. Over the lifetime, 1845 publications have been published within this topic receiving 41398 citations.
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TL;DR: An efficient algorithm for computing radix-3/9 discrete Hartley transforms (DHTs) is presented and it is shown that the Radix- 3/9 fast Hartley transform (FHT) algorithm reduces the number of multiplications required by a radIX-3 FHT algorithm for nearly 50%.
Abstract: An efficient algorithm for computing radix-3/9 discrete Hartley transforms (DHTs) is presented. It is shown that the radix-3/9 fast Hartley transform (FHT) algorithm reduces the number of multiplications required by a radix-3 FHT algorithm for nearly 50%. For the computation of real-valued discrete Fourier transforms (DFTs) with sequence lengths that are powers of 3, it is shown that the radix-3/9 FHT algorithm reduces the number of multiplications by 16.2% over the fastest real-valued radix-3/9 fast Fourier transform (FFT) algorithm. >
9 citations
04 Dec 2007
TL;DR: A hardware interpretation to design a highly parallel and parameterized architecture of the cyclotomic FFT based on four stages and modular structure of last stage which allows to reach a very high throughput rate which, for 256-point FFT, can get hold of 8.5 fc.
Abstract: The hardware design and implementation of cyclotomic Fast Fourier Transform (FFT) over finite fields GF(2m) is described. By reformulating the algorithm presented in [8], we introduce a hardware interpretation to design a highly parallel and parameterized architecture of the cyclotomic FFT. Based on four stages and modular structure of last stage, this architecture can operate at different throughput rates. Compared to another implemented algorithm [9] which operates at fc (the system clock frequency), the proposed architecture allows to reach a very high throughput rate which, for 256-point FFT, can get hold of 8.5 fc. An FPGA implementation of the proposed architecture is given where the critical path delay and the hardware complexity are evaluated.
9 citations
01 Jan 2016
TL;DR: This tutorial describes how to accurately measure signal power using the FFT and the different effects that introduce errors during FFT processing are described and how they can be avoided or compensated.
Abstract: This tutorial describes how to accurately measure signal power using the FFT. The different effects that introduce errors during FFT processing are described and it is explained how they can be avoided or compensated.
9 citations
Patent•
22 Feb 2007TL;DR: In one embodiment, the present invention relates to an interleaved method for computing a Fast Fourier Transform (FFT), and in another embodiment, the authors relates to a method for parallel filter via Fast FFT.
Abstract: The present invention generally relates to a method for computing a Fast Fourier Transform (FFT). In one embodiment, the present invention relates to an interleaved method for computing a Fast Fourier Transform (FFT). In another embodiment, the present invention relates to a method for parallel filter via Fast Fourier Transform (FFT).
9 citations
TL;DR: In this article, the disadvantages of numerical inversion of the Laplace transform via the conventional fast Fourier transform (FFT) are identified and an improved method is presented to remedy them.
Abstract: The disadvantages of numerical inversion of the Laplace transform via the conventional fast Fourier transform (FFT) are identified and an improved method is presented to remedy them. The improved method is based on introducing a new integration step length Delta(omega) = pi/mT for trapezoidal-rule approximation of the Bromwich integral, in which a new parameter, m, is introduced for controlling the accuracy of the numerical integration. Naturally, this method leads to multiple sets of complex FFT computations. A new inversion formula is derived such that N equally spaced samples of the inverse Laplace transform function can be obtained by (m/2) + 1 sets of N-point complex FFT computations or by m sets of real fast Hartley transform (FHT) computations.
9 citations