A Guaranteed Stable Sliding Discrete Fourier Transform Algorithm to Reduced Computational Complexities

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2015 by IJETT Journal
Volume-30 Number-7
Year of Publication : 2015
Authors : Naveen Kumar, Dr. Rajesh Mehra, Buddhi Prakash Sharma
DOI :  10.14445/22315381/IJETT-V30P264

Citation 

Naveen Kumar, Dr. Rajesh Mehra, Buddhi Prakash Sharma"A Guaranteed Stable Sliding Discrete Fourier Transform Algorithm to Reduced Computational Complexities", International Journal of Engineering Trends and Technology (IJETT), V30(7),346-350 December 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Discrete Fourier Transform (DFT) and Fast Fourier Transform is important in the field of Digital Signal Processing, communication and filtering. But now a new concept comes in Digital signal processing is Sliding Discrete Fourier Transform. In this process the Transform window is shifted one sample at a time and this transform process is repeated continuously. In this paper: Background and implementation issues, and the advantages and disadvantages of the Sliding Discrete Fourier Transform(SDFT) as compared with a more traditional Fast Fourier Transform (FFT). The Sliding Discrete Fourier Transform (SDFT) is computationally stable but it also have some errors and potential instabilities. A much more efficient Simple Sliding Inverse DFT that makes sliding a serious alternative to jumping between overlapping frames. In digital signal processing (DSP) by applying a Sliding Discrete Fourier Transform (SDFT) technique we are removing ripple in side lobes of a spectrum. In this method we receive an input signal which includes a number of discrete samples taken at regular time intervals, So as to remove the potential instabilities and errors. Finally we assess the quality of transformations based on the Sliding Discrete Fourier Transform (SDFT).

 References

[1] E. Jacobsen and R. Lyons, “The Sliding DFT", IEEE Signal Processing Magazine”, pp. 74-80, March 2003.
[2] E.Jacobsen and P.Kootsookos, “Fast Accurate Freq- uency Estimators”, IEEE Trans.Signal Process, Vol. 24, pp. 123-125, May 2007.
[3] E. Jacobsen and R. Lyons, “An update to the Sliding DFT", IEEE Signal Processing Magazine, pp.110-111 Jan.2004.
[4] T. Springer, “Sliding FFT computes frequency spectra in real time”, EDN Mag., pp. 161-170, Sept. 29, 1988.
[5] J. Proakis and D. Manolakis, “Digital Signal Proces- sing Principles, Algorithms and Applications”, pp.480 -481, Prentice Hall.
[6] Pooja Kataria , Rajesh Mehra, “Comparative Analysis of FFT Algorithm for different windowing Techniques”, International Journal of Science, Engineering and Technology Research (IJSETR), Vol. 2, Issue 9, September 2013.
[7] A. Nuttall, "Some windows with very good sidelobe behavior", IEEE Trans. Acoust., Speech, Signal Process- ing, Vol. 29, pp.84 -91, Feb. 1981.
[8] S. Douglas and J. Soh, "A numerically stable sliding-window estimator and its application to adaptive filters", Proc. 31st Annual Asilomar Conf. on Signals, Systems, and Computers, Vol. 1, pp.111 - 115, 1997.
[9] B. Farhang-Boroujeny and Y. Lim, "A comment on the computational complexity of sliding FFT", IEEE Trans. Circuits Syst. II, Vol. 39, no. 12, pp.875 -876, 1992.
[10] Jacobsen, Eric and Richard Lyons, “Sliding Spectrum Analysis”, streamlining digital signal processing a tricks of the trade guidebook, 2012.
[11] Duda, Krzysztof, “ Accurate Guaranteed Stable, sliding Discrete Fourier Transform, DSP Tips and Tricks”, IEEE Signal Processing Magazine, 2010.
[12] Duda , Krzysztof, “ Accurate, Guaranteed-Stable, Sliding DFT, Streamlining Digital Signal Processing A Tricks of the Trade Guidebook”, 2012.

Keywords
Frequency Estimation, DFT, FFT, Sliding, Windowing.