Implementation of Multiplierless High-Speed Low Power Split Radix SDF FFT using NEDA Algorithm for Speech Enhancement

Implementation of Multiplierless HighSpeed Low Power Split Radix SDF FFT using NEDA Algorithm for Speech Enhancement

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© 2021 by IJETT Journal
Volume-69 Issue-12
Year of Publication : 2021
Authors : Mr.C.Ramesh Kumar, Dr.M.P.Chitra
DOI :  10.14445/22315381/IJETT-V69I12P209

How to Cite?

Mr.C.Ramesh Kumar, Dr.M.P.Chitra, "Implementation of Multiplierless HighSpeed Low Power Split Radix SDF FFT using NEDA Algorithm for Speech Enhancement," International Journal of Engineering Trends and Technology, vol. 69, no. 12, pp. 66-73, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I12P209

Abstract
The Split Radix FFT processor is primarily used for low-power FFT processors. It necessitates fewer mathematical operations. FFT, in the traditional sense, demands greater power and area. However, the proposed SDF SRFFT approach uses less power, is faster, and has a shorter delay. In addition, the twiddle factor multiplication in this SRFFT is performed using the New Distributed Arithmetic (NEDA) technique, which lowers the chip area. The SRFFT implementation is designed with the XILINX ISE Tool and implemented on FPGA Spartan6. For various types of acoustic noise, the SNR is improved. Python3 is used to lower voice noise using the suggested SRFFT architecture.

Keywords
Fast Fourier Transform, Butter Fly Unit, Processing Element, Single Delay Feedback, New Distributed Arithmetic, Distributed Arithmetic.

Reference
[1] Cooley, J., & Tukey, J., An algorithm for the machine calculation of complex Fourier series. Mathematical Comparative,19 (1965) 297–301.
[2] N. Weste and D. J. Skellern, VLSI for OFDM, IEEE Common. Mag., 36 (1998) 127–131.
[3] Good, I., The interaction algorithm and practical Fourier analysis. Journal of the Royal Statistical Society, B-20 (1958) 361–372
[4] Winograd, S., On computing the discrete Fourier transform. Proceedings of the National Academy of science, (1976).
[5] Sciences of the United States of America, 73, 1005–1006.Morris, L., A comparative study of time-efficient FFT and WFTA programs for general-purpose computers. IEEE Transaction Acoustics Speech Signal Process, ASSP-26 (1978) 141–150
[6] Nawab, H., & McClellan, J., Bounds on the minimum number of data transfers in WFTA and FFT programs. IEEE Transaction Acoustics Speech Signal Process, ASSP-27 (1979) 394–398.
[7] Chen, T., Sunanda, T.G., Jin, J., COBRA: a 100-MOPS single-chip programmable and expandable FFT. IEEE Transactions Very Large Scale Integrative (VLSI) Systems, 7 (1999) 174–182.
[8] Maharatna, G., &Jagdhold, U., A 64-point Fourier transform chip for high-speed wireless LAN application using OFDM. IEEE Journal Solid-State Circuits, 39 (2004) 484–493.
[9] Perez-Pascual, A., Sanaloni, T., Valls, J., FPGA-based radix-4 butterflies for HIPERLAN/2. In IEEE international symposium on circuits and systems , (2002) 277–280.
[10] Duhamel, P., & Hollmann, H., Implementation of split radix FFT algorithms for complex, real, and real-symmetric data.IEEE International Conference on Acoustics, Speech and Signal Processing, 10 (1985) 784–787
[11] Jiang, M., Yang, B., Huang, R., Zhang, T.Y., Wang, Y.Y.,Multiplierless fast Fourier transform architecture. Electronics Letters,43 (2007) 191–192.
[12] Maharatna, G., &Jagdhold, U., A 64-point Fourier transform chip for high-speed wireless LAN application using OFDM. IEEE Journal Solid-State Circuits, 39 (2004) 484–493.
[13] Zohar, S., The counting recursive digital filter. IEEE Transaction on Computers, C-22 (1973) 338–347.
[14] Joshi, S.P., Paily, R. Distributed Arithmetic based Split-Radix FFT. J Sign Process Syst 75 (2014) 85–92.
[15] Duhamel, P., & Hollmann, H., Implementation of split-radix FFT algorithms for complex, real, and real-symmetric data. IEEE International Conference on Acoustics, Speech and Signal Processing (1985).
[16] Ansuman Dipti Sankar Das, Abhishek Mankar, N Prasad, K. K. Mahapatra, Ayas Kanta Swain, Efficient VLSI Architectures of Split-Radix FFT using New Distributed Arithmetic, International Journal of Soft Computing and Engineering (IJSCE), (2013).
[17] Wendi Pan, Ahmed Shams, and Magdy A. Bayoumi, NEDA: A New Distributed Arithmetic Architecture and its Application to One Dimensional Discrete Cosine Transform,
[18] Y. Wang, Research Progress in Speech Enhancement Technology, 2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL), (2020) 222-226,
[19] M. Chen and K. -J. Chen, Research on Novel Normal Fuzzy Kalman Filter for Speech Enhancement in Noisy Environment, IEEE International Conference on Power Electronics, Computer Applications (ICPECA), (2021).
[20] G. M. Rao and U. S. Kumar, Speech enhancement using a combination of digital audio effects with Kalman filter, 2016 International Conference on Signal Processing, Communication, Power, and Embedded System (SCOPES), (2016).
[21] Hari Narayan Mishra, Agya Mishra Agya Mishra, Audio Enhancement using Remez Exchange Algorithm with DWT, IJETT International Journal of Electronics and Communication Engineering (IJETT-IJECE) – 2(2) (2015).
[22] P.Kabilamani, Dr.C.GomathyEfficient Modified Reduced FFT(MRFFT) Feedback-Commutator Architecture Design, IJETT International Journal of VLSI & Signal Processing (IJETT - IJVSP) - Volume 6(1) (2019).