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Efficient VLSI Architecture for DIT and DIF Fast Fourier Transform using Real Valued Data

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Neeraj Kumar Pandey, Pankaj Soni
10.5120/ijca2017914406

Neeraj Kumar Pandey and Pankaj Soni. Efficient VLSI Architecture for DIT and DIF Fast Fourier Transform using Real Valued Data. International Journal of Computer Applications 167(8):29-32, June 2017. BibTeX

@article{10.5120/ijca2017914406,
	author = {Neeraj Kumar Pandey and Pankaj Soni},
	title = {Efficient VLSI Architecture for DIT and DIF Fast Fourier Transform using Real Valued Data},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {8},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {29-32},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume167/number8/27795-2017914406},
	doi = {10.5120/ijca2017914406},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

With the upcoming of new innovation in the fields of VLSI and correspondence, there is additionally a perpetually developing interest for fast preparing and low territory outline. It is additionally a verifiable truth that the chip range and most propagation time unit shapes a necessary piece of processor outline. Because of this respect, rapid and low zone designs turn into the need of the day. A fast fourier transform (FFT) is any quick calculation for figuring the DFT. The advancement of FFT calculations tremendously affected computational parts of flag handling and connected science. The decimation in-time (DIT) fast Fourier transform (FFT) all the time has advantage over the decimation in-frequency (DIF) FFT for most genuine esteemed applications, similar to discourse/picture/video handling, biomedical flag preparing, and time-arrangement examination, and so forth., since it doesn't require any yield reordering.

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Keywords

FFT, MCPD, LUT, Decimation in Time, Decimation in Frequency, real Value data.