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.

Fast sparse 2-D DFT computation using sparse-graph alias codes

Abstract: We present a novel algorithm, named the 2D-FFAST (Two-dimensional Fast Fourier Aliasing-based Sparse Transform), to compute a sparse 2D-Discrete Fourier Transform (2D-DFT) featuring both low sample and computational complexity. The proposed algorithm is based on diverse concepts from signal processing (sub-sampling and aliasing), coding theory (sparse-graph codes) and number theory (Chinese-remainder-theorem) and generalizes the 1D-FFAST algorithm recently proposed by Pawar and Ramchandran [1, 2] to the 2D setting. Concretely, our proposed 2D-FFAST algorithm computes a k-sparse 2D-DFT, with a uniformly random support, of size N = Nx × Ny using O(k) noiseless spatial-domain measurements in O(k log k) computational time. Our results are attractive when the sparsity is sub-linear with respect to the signal dimension, that is, when k _ ∞ and k/N → 0. For the case when the spatial-domain measurements are corrupted by additive noise, our 2D-FFAST framework extends to a noise-robust version of computing a 2D-DFT using O(k log3 N) measurements in sub-linear time of O(klog4 N). Empirically, we show that the 2D-FFAST can compute a k = 3509 sparse 2D-DFT of a 508 × 508-size phantom image using only 4.75k measurements. We also empirically evaluate the 2D-FFAST algorithm on a real-world magnetic resonance brain image using a total of 60.18% of Fourier measurements to provide an almost instant reconstruction with SNR=4.5 dB. This provides empirical evidence that the 2D-FFAST architecture is applicable to a wider class of input signals than analyzed theoretically in the paper.

A sparse data fast Fourier transform (SDFFT)

Abstract: A multilevel algorithm that efficiently Fourier transforms sparse spatial data to sparse spectral data with controllable error is presented. The algorithm termed "sparse data fast Fourier transform" (SDFFT) is particularly useful for signal processing applications where only part of the k-space is to be computed - regardless of whether it is a regular region like an angular section of the Ewald sphere or it consists of completely arbitrary points scattered in the k-space. In addition, like the various nonuniform fast Fourier transforms, the O(NlogN) algorithm can deal with a sparse, nonuniform spatial domain. In this paper, the parabolic reflector antenna problem is studied as an example to demonstrate its use in the computation of far-field patterns due to arbitrary aperture antennas and antenna arrays. The algorithm is also promising for various applications such as backprojection tomography, diffraction tomography, and synthetic aperture radar imaging.

Parameter identification of time-delay systems via exponential Fourier series

Abstract: A delay matrix D is derived and used along with the exponential Fourier operational matrix of integration in a new algorithm for parameter identification of LTI delayed systems. The main advantage of this method over similar algorithms is that Fast Fourier Transform (FFT) can be employed for determining expansion coefficients. Therefore, it reduces the computing time considerably. A second advantage is that the Fourier delay and integration matrices are simpler than their counterparts associated with other orthogonal functions. This further reduces compulations. An example is given which shows that the algorithm gives accurate parameter estimates.

A New Prime Edge Length Crystallographic FFT

Abstract: A new method for computing the discrete Fourier transform (DFT) of data endowed with linear symmetries is presented. The method minimizes operations and memory space requirements by eliminating redundant data and computations induced by the symmetry on the DFT equations. The arithmetic complexity of the new method is always lower, and in some cases significantly lower than that of its predecesor. A parallel version of the new method is also discussed. Symmetry-aware DFTs are crucial in the computer determination of the atomic structure of crystals from x-ray diffraction intensity patterns.

FPGA Implementation of High Speed FFT Algorithm Based on Split-Radix

Abstract: Fast Fourier transform (FFT) is the collection of algorithms that performed the discrete Fourier transform (DFT). As a medium to perform the transform from time domain to frequency domain, FFT is widely used as an indispensible tool in signal processing applications. Split-radix algorithm is an appropriate algorithm for the implementation of FFT among all the effective algorithms of FFT. At the requirement of high speed, an algorithm that is best for high speed implementation is to be found. After researching all the relative algorithms, split-radix algorithm is chosen as the basic algorithm. In this paper, parallel processing and pipeline techniques are employed and proved to be a well-performed method. The proposed method performs well in the implementation of FPGA and satisfies the requirement of high speed. Results show the system latency of 13 clock periods and high efficiency in conserving hardware resources. The method put forward in this paper is extensible and can be applied to various applications.