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Prime-factor FFT algorithm

About: Prime-factor FFT algorithm is a research topic. Over the lifetime, 2346 publications have been published within this topic receiving 65147 citations. The topic is also known as: Prime Factor Algorithm.


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Proceedings ArticleDOI
11 Jun 1991
TL;DR: An efficient radix-3/9 fast Hartley transform (FHT) algorithm is proposed, which shows a great improvement over the previous radIX-3 FHT algorithm such that nearly 50% of the number of multiplications is saved.
Abstract: An efficient radix-3/9 fast Hartley transform (FHT) algorithm is proposed. It shows a great improvement over the previous radix-3 FHT algorithm such that nearly 50% of the number of multiplications is saved. For the computation of real-valued DFTs (discrete Fourier transforms) with sequence lengths which are powers of 3, the proposed radix-3/9 algorithm gives an average of 16.2% reduction in the number of multiplications over the fastest radix-3/9 FFT (fast Fourier transform) algorithm. The improvement is mainly the result of the simplicity of the computing structure of the proposed algorithm and the use of fast length-3 and fast length-9 DHT modules. >
Proceedings ArticleDOI
14 Apr 1991
TL;DR: Instead of the row-column algorithm which was designed based on the 1D FFT, an algorithm based on 1D cyclic convolution is designed and it is shown that this algorithm is efficient for some sample points and flexible for parallel or vector processing.
Abstract: Two algorithms for the 2D fast Fourier transform (FFT) are developed, where the prime size p identical to 3 mod 4 and p identical to 2 mod 3. The indexing set in each case forms a field, and the computation of the 2D FFT can be completely transferred into one dimension which is identical to the computational structure of the 1D FFT with prime size. Instead of the row-column algorithm which was designed based on the 1D FFT, an algorithm based on 1D cyclic convolution is designed. It is shown that this algorithm is efficient for some sample points and flexible for parallel or vector processing. >
Proceedings ArticleDOI
03 Jul 2005
TL;DR: In this article, the authors investigated an efficient method to speed up the linear inverse scattering with the aid of the fast Fourier transform (FFT) and compared the computational complexity between the usual CG method and the CG-FFT method.
Abstract: Electromagnetic inverse scattering is very important for a number of sensing and remote sensing applications. However, since the inverse scattering problem is ill-posed, a large number of iterations are required when using the conjugate gradient (CG) scheme. In this work, we investigate an efficient method to speed up the linear inverse scattering with the aid of the fast Fourier transform (FFT). We discuss how to perform 2D FFT in the CG method for the inverse-scattering problem and compare the computational complexity between the usual CG method and the CG-FFT method. Finally, reconstruction results are given, which show that the proposed algorithm can be used to solve large-scale inverse problems efficiently.
Proceedings ArticleDOI
28 Dec 2022
TL;DR: In this paper , the authors proposed a novel architecture for N-point FFT with run-time configurable Radix-2 architecture, FFT size, and data type, and implemented the logic so that only one memory will be used for the entire computation process.
Abstract: A Fast Fourier Transform is an efficient algorithm to compute the discrete Fourier Transform (DFT). It is one of the finest operations in the area of digital signal and image processing. The operation requires a high computational module i.e., (N 2 complex multiplications and N*(N-1) additions). This makes the computational and implementation very difficult. Implementation of N-point FFT/IFFT of data width 32-bit (16-bit real and 16-bit Imaginary) with run-time configurable Radix-2 Architecture, FFT size, and data type i.e., (Fixed Point). Compile time configurable data and twiddle factor precision. The design target is to minimize the latency and design constraints. The logic is implemented so that only one memory will be used for the entire computation process. Hence, this gives a Novel architecture design for N-point FFT.
Proceedings ArticleDOI
01 Oct 2016
TL;DR: For the Sinusoid Signals with additive Gauss white noise, a frequency estimation algorithm based on discrete Fourier transform (DFT) interpolation algorithm is proposed in this paper and the performance of the proposed algorithm is better and more stable under the same conditions.
Abstract: For the Sinusoid Signals with additive Gauss white noise, a frequency estimation algorithm based on discrete Fourier transform (DFT) interpolation algorithm is proposed in this paper. Based on the classical interpolation algorithm, the algorithm of this paper takes full use of the Peak Spectral Frequency and its neighbor spectral lines to estimate the frequency of the signal. The analysis and simulation results indicate that the performance of the algorithm approaching to the Cramer-Rao lower bound (CRLB) when the signal to noise ratio (SNR) is above −5 dB. Compared with the classical Rife algorithm, the performance of the proposed algorithm is better and more stable under the same conditions. Besides the algorithm is easy to implement and apply with low computational complexity.

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20235
202224
20211
20188
201757
201692