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.

Application of the fast Fourier number theoretic transform to radar

Abstract: Radar applications of the multiple radix fast Fourier number theoretic transform (FFT/NTT) are discussed. The FFT/NTT performs a prime length discrete Fourier transform (DFT) efficiently and accurately using NTTs. The FFT/NTT produces an output without any internal truncation or rounding; therefore, it follows that use of the FFT/NTT for radar processing should yield improvements in the radar's detection performance over some FFT implementations. It is shown that a FFT/NTT computed with n bits yielded equivalent performance to a 2/sup m/-point FFT which processed n+m bits. The FFT/NTT can be easily reconfigured to process additional input bits, thus allowing for increased clutter rejection. >

Instruction set processor enhancement for computing a fast fourier transform

Abstract: This invention describes a method of computing a fast Fourier transform (FFT) using enhanced processor computational capabilities for more efficient and flexible implementation of an electronic device (e.g., a linear equalizer) based on that FFT computing. A simple non-parallel instruction set processor (or just a non-parallel processor) containing complex multiplication and addition/subtraction capabilities is extended by adding additional registers and interconnects and a dedicated parallel instruction for calculating the FFT butterfly. The parallel instruction consists of orthogonal sub-instructions each controlling a section of the data path related to a corresponding section of the FFT butterfly.

A New Method for m-sequence and Gold-sequence Generator Polynomial Estimation

Abstract: A finite field discrete Fourier transform is used for studying the properties of linear feedback shift register (LFSR) sequence with period (q1-1)/n, and the elation of sequence' s linear complexity and the nonzero-points in frequency-domain is given in this paper. Then a new algorithm is introduced to estimate the generator polynomial and initial state of m-sequence and gold-sequence. Based on the principle of FFT, a fast algorithm is also explored.

Asymmetry DFT Algorithm and Its Application

Abstract: In order to get good statistical properties,the DFT(Discrete Fourier Transform) algorithm requires the number of time-domain sampling points N is big enough,but the bigger N is,the bigger the amount of computation is.For the characteristic that the harmonic frequency is much less than the number of time-domain sampling points in harmonics analysis of power system,the asymmetry DFT algorithm is proposed to be applicable for the harmonics analysis of power system.It is demonstrated in the theory that the result the new algorithm gives is just the least squares estimation of harmonics coefficients.The application of the new algorithm in harmonics analysis of power system is studied.The research results prove the asymmetry DFT algorithm not only costs less time in the calculation,but also has better statistical properties than the standard FFT algorithm.

Parallel implementations of 1-D fast Fourier transform without interprocessor communication

Abstract: Computing 1-D Fast Fourier Transform (FFT) using the conventional 4-step FFT on parallel computers requires intensive all-to-all communication, which can adversely affect the performance of FFT. In this paper, we present 2-step-no-communication and 3-step-no-communication algorithms, which are parallel algorithms for 1-D FFT without interprocessor communication. One of the main advantages of these algorithms is the absence of all-to-all communication between processors, albeit at the expense of increased computation compared to the conventional 4-step FFT. If the cost of extra computation required by the 2-step-no-communication and the 3-step-no-communication algorithms is more than offset by the cost of all-to-all communication in the 4-step FFT, then these two no-communication algorithms will outperform the 4-step FFT algorithm. We test the 2-step-no-communication and the 3-step-no-communication algorithms in two parallel systems (a 32-node Beowulf cluster and 8-node symmetric multiprocessors), with varying costs of all-to-all communication and computation. The experimental results show that the no-communication algorithms perform better than the 4-step FFT in the SMP only for relatively small data sizes, but the no-communication algorithms outperform the 4-step FFT in the Beowulf cluster for all data sizes tested.