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Reseach Article

Multiplier-less Farrow Structure based Linear Phase Low Pass Interpolation Filter

by Nisha Haridas, Aravind Illa, Elizabeth Elias
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 14
Year of Publication: 2014
Authors: Nisha Haridas, Aravind Illa, Elizabeth Elias
10.5120/16659-6645

Nisha Haridas, Aravind Illa, Elizabeth Elias . Multiplier-less Farrow Structure based Linear Phase Low Pass Interpolation Filter. International Journal of Computer Applications. 95, 14 ( June 2014), 1-6. DOI=10.5120/16659-6645

@article{ 10.5120/16659-6645,
author = { Nisha Haridas, Aravind Illa, Elizabeth Elias },
title = { Multiplier-less Farrow Structure based Linear Phase Low Pass Interpolation Filter },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 14 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number14/16659-6645/ },
doi = { 10.5120/16659-6645 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:19:25.337219+05:30
%A Nisha Haridas
%A Aravind Illa
%A Elizabeth Elias
%T Multiplier-less Farrow Structure based Linear Phase Low Pass Interpolation Filter
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 14
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper proposes a totally multiplier-less farrow structure based linear phase low-pass interpolation filter. When implemented using farrow structure, it has inherently low number of multipliers and adders compared to that using finite impulse response (FIR) filter structure. To further reduce the implementation complexity, the structure is made totally multiplier-less. Canonic signed digit (CSD) representation of the filter coefficients is made use of in this paper. A meta-heuristic optimization algorithm is deployed to obtain optimal CSD representation. Reduction in the implementation complexity leads to lower power consumption, chip area and cost.

References
  1. H Johansson and O Gustafsson. Linear-phase fir interpolation, decimation, and mth-band filters utilizing the farrow structure. Circuits and Systems I: Regular Papers, IEEE Transactions on, 52(10):2197–2207, 2005.
  2. C W Farrow. A continuously variable digital delay element. In Circuits and Systems, 1988. , IEEE International Symposium on, pages 2641–2645. IEEE, 1988.
  3. J Vesma and T Saramaki. Optimization and efficient implementation of fir filters with adjustable fractional delay. In Circuits and Systems, 1997. ISCAS'97. , Proceedings of 1997 IEEE International Symposium on, volume 4, pages 2256– 2259. IEEE, 1997.
  4. H Johansson and P Lowenborg. On the design of adjustable fractional delay fir filters. Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on, 50(4):164– 169, 2003.
  5. H°akan Johansson. Farrow-structure-based reconfigurable bandpass linear-phase fir filters for integer sampling rate conversion. Circuits and Systems II: Express Briefs, IEEE Transactions on, 58(1):46–50, 2011.
  6. Amir Eghbali and H°akan Johansson. Reconfigurable twostage nyquist filters utilizing the farrow structure. In ISCAS, pages 3186–3189, 2012.
  7. Amir Eghbali and H°akan Johansson. A class of reconfigurable and low-complexity two-stage nyquist filters. Signal Processing, 96:164–172, 2014.
  8. M Manuel and E Elias. Design of frequency response masking fir filter in the canonic signed digit space using modified artificial bee colony algorithm. Engineering Applications of Artificial Intelligence, 26(1):660–668, 2013.
  9. TS Bindiya and E Elias. Design of multiplier-less reconfigurable non-uniform channel filters using meta-heuristic algorithms. International Journal of Computer Applications, 59, 2012.
  10. B Webb. Swarm intelligence: From natural to artificial systems. 2002.
  11. D Karaboga. An idea based on honey bee swarm for numerical optimization. Technical report, Technical report-tr06, Erciyes university, engineering faculty, computer engineering department, 2005.
  12. VJ Manoj and E Elias. Artificial bee colony algorithm for the design of multiplier-less nonuniform filter bank transmultiplexer. Information Sciences, 192:193–203, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Farrow Interpolation Filter Integer Sampling rate conversion ABC optimization Canonic Signed Digit