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Author Ranganadh, Narayanam ♦ Muni Guravaiah, P.
Source CiteSeerX
Content type Text
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Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Grigoryan Fft ♦ Virtex-5 Fpgas ♦ Performance Evaluation ♦ Xilinx Virtex-ii Pro ♦ Cooley Tukey Fft ♦ Sampling Rate ♦ Discrete Fourier Transform ♦ Principal Mathematical Method ♦ Frequency Analysis ♦ Fouriertransformed Data ♦ Brain Stem Speech ♦ Image Processing ♦ Audio Recording ♦ Fast Algorithm ♦ Voice Activity Detection ♦ Signal Processing Technique ♦ Speech Processing Spectrogram ♦ Paired Transform ♦ Phonetic Sound ♦ Simple Way ♦ Cooley-tukey Fft ♦ Neurological Signal ♦ Large Family ♦ Dsp Application ♦ Xilinx Virtex-ii ♦ Fourier Frequency Analysis ♦ Index Term Frequency Analysis ♦ Artefact Removal ♦ X-ray Crystallography ♦ Fft Processor Architecture
Abstract Abstract- A large family of signal processing techniques consist of Fourier-transforming a signal, manipulating the Fouriertransformed data in a simple way, and reversing the transformation. We widely use Fourier frequency analysis in equalization of audio recordings, X-ray crystallography, artefact removal in Neurological signal and image processing, Voice Activity Detection in Brain stem speech evoked potentials, speech processing spectrograms are used to identify phonetic sounds and so on. Discrete Fourier Transform (DFT) is a principal mathematical method for the frequency analysis. The way of splitting the DFT gives out various fast algorithms. In this paper, we present the implementation of two fast algorithms for the DFT for evaluating their performance. One of them is the popular radix-2 Cooley-Tukey fast Fourier transform algorithm (FFT) [1] and the other one is the Grigoryan FFT based on the splitting by the paired transform [2]. We evaluate the performance of these algorithms by implementing them on the Xilinx Virtex-II pro [3] and Virtex-5 [4] FPGAs, by developing our own FFT processor architectures. Finally we show that the Grigoryan FFT is working fatser than Cooley-Tukey FFT, consequently it is useful for higher sampling rates. Operating at higher sampling rates is a challenge in DSP applications. Index Terms- frequency analysis, fast algorithms, DFT, FFT, paired transforms.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article