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.

Efficient architecture for real time implementation of Hilbert Transform in FPGA

Abstract: This paper presents an architecture for real time hardware implementation of Hilbert Transform (HT) using Fast Fourier Transform (FFT). HT is studied and its various application areas are discussed in the paper. Two different architectures are proposed using Fast Fourier Transform (FFT) for the implementation. Implementation of HT using the proposed FFT based architectures are compared with the implementations using Discrete Fourier Transform (DFT) and Discrete Hartley Transform (DHT). The proposed FFT based architectures are implemented on Xilinx Kintex- 7 based FPGA and the results acquired are presented in comparison to results obtained through MATLAB simulations. The architecture implemented supports transform length of 8192 points as a demonstrator to the idea using 24 bit fixed point arithmetic. Detailed comparison study in terms of resource utilization and timing analysis is also carried out and the results are reported.

An improved fast Fourier transform algorithm using mixed frequency and time decimations

Abstract: An improved FFT (fast Fourier transform) algorithm combining both decimations in frequency and in time is presented. Stress is placed on a derivation of general formulas for submatrices and multiplicands. Computational efficiency is briefly discussed. >

Comparison of different FFT implementations in the encrypted domain

Abstract: Signal processing modules working directly on the encrypted data could provide an elegant solution to application scenarios where valuable signals should be protected from a malicious processing device. In this paper, we compare different implementations of the discrete Fourier transform (DFT) in the encrypted domain. Both radix-2 and radix-4 fast Fourier transforms (FFTs) will be defined using the homomorphic properties of the underlying cryptosystem. We derive the maximum size of the sequence that can be transformed by using the different implementations and we provide computational complexity analyses and comparisons. The results show that the radix-4 FFT is best suited for an encrypted domain implementation.

A Power Quality Analysis Method Based on Mallat Algorithm and Fast Fourier Transform

Abstract: Based on Mallat algorithm and fast Fourier transform (FFT), the authors propose a power quality analysis method. In this method, the wavelet denoising is applied to sampled signals; according to the detection results of catastrophe point of signals, the high frequency coefficients of the first level and the second level obtained by Mallat decomposition algorithm are taken as the criteria to distinguish steady state disturbance from non-steady state disturbance, and then the duration of disturbance can be solved. In the light of frequency band division principle of multi-resolution analysis, by use of Mallat reconstruction algorithm the transient disturbance waveform is extracted, moreover an identification subroutine that can accurately distinguish short-term variation disturbances such as voltage sag, voltage swell and interruption is programmed. For steady state disturbance, the authors point out that FFT can be used as a tool to distinguish harmonics from flicker. The effectiveness and accuracy of the proposed method is validated by Matlab-based simulation results.

Fft based solution for multivariable l2 equations using kkt system via fft and efficient pixel-wise inverse calculation

Abstract: When solving l 2 optimization problems based on linear filtering with some regularization in signal/image processing such as Wiener filtering, the fast Fourier transform (FFT) is often available to reduce its computational complexity. Most of the problems, in which the FFT is used to obtain their solutions, are based on single variable equations. On the other hand, the Karush-Kuhn-Tucker (KKT) system, which is often used for solving constrained optimization problems, generally results in multivariable equations. In this paper, we propose a FFT based computational method for multivariable l 2 equations. Our method applies a FFT to each block of the KKT system, and represents the equation as an image-wise simultaneous equation consisting of Fourier transformed filters and images. In our method, an inverse matrix calculation that consists of complex pixel values gathered from each transformed image is required for each pixel. We exploit the homogeneity of neighboring values and solve them efficiently.