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Reseach Article

Article:Feasibility Analysis and Comparative study of FFT & Autocorrelation Algorithms

by Abhishek Shukla, Suraj S. Jibhakate
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 7 - Number 9
Year of Publication: 2010
Authors: Abhishek Shukla, Suraj S. Jibhakate
10.5120/1277-1615

Abhishek Shukla, Suraj S. Jibhakate . Article:Feasibility Analysis and Comparative study of FFT & Autocorrelation Algorithms. International Journal of Computer Applications. 7, 9 ( October 2010), 20-24. DOI=10.5120/1277-1615

@article{ 10.5120/1277-1615,
author = { Abhishek Shukla, Suraj S. Jibhakate },
title = { Article:Feasibility Analysis and Comparative study of FFT & Autocorrelation Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { October 2010 },
volume = { 7 },
number = { 9 },
month = { October },
year = { 2010 },
issn = { 0975-8887 },
pages = { 20-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume7/number9/1277-1615/ },
doi = { 10.5120/1277-1615 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:55:52.550539+05:30
%A Abhishek Shukla
%A Suraj S. Jibhakate
%T Article:Feasibility Analysis and Comparative study of FFT & Autocorrelation Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 7
%N 9
%P 20-24
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

FFT is one main property in any sequence being used in general. To find this property of FFT for any given sequence, many transforms are being used. The major issues to be noticed in finding this property are the time and memory management. Two different algorithms are written for calculating FFT and Autocorrelation of any given sequence. Comparison is done between the two algorithms with respect to the memory and time managements and the better one is pointed. Comparison is between the two algorithms written, considering the time and memory as the only main constraints. Time taken by the two transforms in finding the fundamental frequency is taken. At the same time the memory consumed while using the two algorithms is also checked. Based on these aspects it is decided which algorithm is to be used for better results.

References
  1. [paper] matlab implementation of an fft based algorithm for polynomial plus/minus factorization by martin hromcık, michael sebek
  2. [paper] systematic generation of fpga-based fft implementations hojin kee, newton petersen, jacob kornerup, shuvra s. bhattacharyya.
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  6. IEEE Oceanic Engineering Societyby ,MacInnes, C.S. Alameda El Espinel, Lima
  7. hojin kee, newton petersen, jacob kornerup, shuvra s. bhattacharyya,” systematic generation of fpga-based fft implementations”, in proceedings of the international conference on acoustics, speech, and signal processing,las vegas, nevada, march 2008.
  8. josé moura, carnegie mellon university” dsp formatlab™ and labview™ volume ii: discrete frequencytransforms”, foresterw. isen 2008
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  10. web resource: [online source visited on sept 07,2010] jorg arndt ,”algorithms for programmers”; this document is online at http://www.jjj.de/fxt/.
Index Terms

Computer Science
Information Sciences

Keywords

FFT (fast fourier transform) Autocorrelation MATLAB C platform Time management Memory management