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.

Correcting soft errors online in fast fourier transform

Abstract: While many algorithm-based fault tolerance (ABFT) schemes have been proposed to detect soft errors offline in the fast Fourier transform (FFT) after computation finishes, none of the existing ABFT schemes detect soft errors online before the computation finishes. This paper presents an online ABFT scheme for FFT so that soft errors can be detected online and the corrupted computation can be terminated in a much more timely manner. We also extend our scheme to tolerate both arithmetic errors and memory errors, develop strategies to reduce its fault tolerance overhead and improve its numerical stability and fault coverage, and finally incorporate it into the widely used FFTW library - one of the today's fastest FFT software implementations. Experimental results demonstrate that: (1) the proposed online ABFT scheme introduces much lower overhead than the existing offline ABFT schemes; (2) it detects errors in a much more timely manner; and (3) it also has higher numerical stability and better fault coverage.

Fast algorithm for chirp transforms with zooming-in ability and its applications

Abstract: A general fast numerical algorithm for chirp transforms is developed by using two fast Fourier transforms and employing an analytical kernel. This new algorithm unifies the calculations of arbitrary real-order fractional Fourier transforms and Fresnel diffraction. Its computational complexity is better than a fast convolution method using Fourier transforms. Furthermore, one can freely choose the sampling resolutions in both x and u space and zoom in on any portion of the data of interest. Computational results are compared with analytical ones. The errors are essentially limited by the accuracy of the fast Fourier transforms and are higher than the order 10(-12) for most cases. As an example of its application to scalar diffraction, this algorithm can be used to calculate near-field patterns directly behind the aperture, 0 d2/lambdaN [J. Opt. Soc. Am. A 15, 2111 (1998)]. Experimental results from waveguide-output microcoupler diffraction are in good agreement with the calculations.

Wavelet transform based fast approximate Fourier transform

Abstract: We propose an algorithm that uses the discrete wavelet transform (DWT) as a tool to compute the discrete Fourier transform (DFT). The Cooley-Tukey FFT is shown to be a special case of the proposed algorithm when the wavelets in use are trivial. If no intermediate coefficients are dropped and no approximations are made, the proposed algorithm computes the exact result, and its computational complexity is on the same order of the FFT, i.e. O(N log/sub 2/ N). The main advantage of the proposed algorithm is that the good time and frequency localization of wavelets can be exploited to approximate the Fourier transform for many classes of signals resulting in much less computation. Thus the new algorithm provides an efficient complexity vs. accuracy tradeoff. When approximations are allowed, under certain sparsity conditions, the algorithm can achieve linear complexity, i.e. O(N). The proposed algorithm also has built-in noise reduction capability.

Iterative algorithm for nonuniform inverse fast Fourier transform (NU-IFFT)

Abstract: A nonuniform inverse fast Fourier transform (NU-IFFT) for nonuniformly sampled data is realised by combining the conjugate-gradient fast Fourier transform (CG-FFT) method with the newly developed nonuniform fast Fourier transform (NUFFT) algorithms. An example application of the algorithm in computational electromagnetics is presented.

Memory-efficient and high-speed split-radix FFT/IFFT processor based on pipelined CORDIC rotations

Abstract: The author presents a CORDIC-based split-radix fast Fourier transform (FFT)/inverse FFT (IFFT) processor dedicated to the computation of 2048/4096/8192-point discrete Fourier transforms (DFTs). The arithmetic unit of a butterfly processor and a twiddle factor generator are based on a CORDIC algorithm. An efficient implementation of the CORDIC-based split-radix FFT algorithm is demonstrated. The chip of 2048/4096/8192-point FFT/IFFT core processor is fabricated in a 0.18 µm CMOS technology. The core size is 4860×7883 µm2 and contains about 200 822 gates for logic and memory, and the power dissipation is 350 mW with a clock rate of 150 MHz at 1.8 V. All control signals are generated internally on-chip. The processor performs 8192-point FFT/IFFT every 138 µs and 2048-point FFT/IFFT every 34.5 µs, respectively, which exceeds orthogonal frequency division multiplexer symbol rates. The modified-pipelining CORDIC arithmetic unit is employed for complex multiplication. A CORDIC twiddle factor generator is proposed and implemented for reducing the size of ROM required for storing the twiddle factors. Compared with conventional FFT implementations, the power consumption is reduced by 25%.