Search results for "Prime-factor FFT algorithm"
showing 4 items of 4 documents
An optimized mass storage FFT for vector computers
1995
Abstract The performance of a segmented FFT algorithm which allows the out-of-core computation of the Fourier transform of a very large mass storage data array is presented. The code is particularly optimized for vector computers. Tests performed mainly on a CONVEX C210 vector computer showed that, for very long transforms, tuning of the main parameters involved leads to computation speed and global efficiency better than for FFTs performed in-core. The use of tunable parameters allows optimization of the algorithm on machines with different configurations.
Area-efficient FPGA-based FFT processor
2003
A novel architecture for computing the fast Fourier transform on programmable devices is presented. Main results indicate that the use of one CORDIC operator to perform the multiplication by all the ‘twiddle factors’ sequentially leads to an area saving up to 35% with respect to other cores.
Discrete wavelet transform implementation in Fourier domain for multidimensional signal
2002
Wavelet transforms are often calculated by using the Mallat algorithm. In this algorithm, a signal is decomposed by a cascade of filtering and downsampling operations. Computing time can be important but the filtering operations can be speeded up by using fast Fourier transform (FFT)-based convolutions. Since it is necessary to work in the Fourier domain when large filters are used, we present some results of Fourier-based optimization of the sampling operations. Acceleration can be obtained by expressing the samplings in the Fourier domain. The general equations of the down- and upsampling of digital multidimensional signals are given. It is shown that for special cases such as the separab…
Fractional-Fourier-transform calculation through the fast-Fourier-transform algorithm.
1996
A method for the calculation of the fractional Fourier transform (FRT) by means of the fast Fourier transform (FFT) algorithm is presented. The process involves mainly two FFT’s in cascade; thus the process has the same complexity as this algorithm. The method is valid for fractional orders varying from −1 to 1. Scaling factors for the FRT and Fresnel diffraction when calculated through the FFT are discussed.