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Reseach Article

Design of Band-Pass Filter using Artificial Neural Network

by Shushank Dogra, Narinder Sharma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 89 - Number 1
Year of Publication: 2014
Authors: Shushank Dogra, Narinder Sharma
10.5120/15465-3837

Shushank Dogra, Narinder Sharma . Design of Band-Pass Filter using Artificial Neural Network. International Journal of Computer Applications. 89, 1 ( March 2014), 13-18. DOI=10.5120/15465-3837

@article{ 10.5120/15465-3837,
author = { Shushank Dogra, Narinder Sharma },
title = { Design of Band-Pass Filter using Artificial Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 89 },
number = { 1 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 13-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume89/number1/15465-3837/ },
doi = { 10.5120/15465-3837 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:08:06.582012+05:30
%A Shushank Dogra
%A Narinder Sharma
%T Design of Band-Pass Filter using Artificial Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 89
%N 1
%P 13-18
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

For the design of Band pass FIR filters complex calculations are involved. Mathematically, by substituting the value of pass-band ripple, stop band attenuation, pass-band frequency F1, pass-band frequency F2, sampling frequency in any of the methods from window method, frequency sampling method or optimal method we can get the values of filter coefficients h(n). Here, window method is used in which Kaiser window method has been chosen preferably because of the presence of ripple factor (?). Here, I have design Band pass FIR filter using artificial neural network which gives optimum result i. e. the difference between the actual and desired output is minimum.

References
  1. V. Aggarwal, J. O. Wesley and M. O Una. , (2006) "Filter approximation using Explicit Time and Frequency Remain specification". Procedure, of the Annual Symposium on Artificial Intelligence, 2006, Seattle, Washington, pp. 174–165.
  2. A. M. Cristian and H. Guinther, (2007) "Architecture Optimization of a Finite Impulse Response Filter using togglebased power estimation", International conference, on intelligent and Advance systems, 2007, pp. 1270–1273.
  3. A. Fizelow. , P. Brites. , A. Ochoa. , H. Mertuns. , E. Fernandez, and Garcia-Martinez R. (2007) "Finding Optimal Neural Network Architecture using Genetic Algorithms," Procedure of the encourages in computer and Engineering, 2007, pp. 15–24.
  4. D. Bhattacharya and A. Antoniou, (1996) "Real Time Design of FIR Filters of Feedback Neural Network", Vol. 3, 1996, pp. 1070–1078
  5. D. A. Yasur and R. Teresa. , (2007) "LUT-based Power Macro modeling Technique for DSP architectures", Procedure of the IEEE, Centro de Electronics Industrial, Spain, August, 2007, pp. 1416–1419.
  6. K. B. Englihart, B. S. Hudgins, M. Stevenson and P. A. Parker, (1994) "Myoelectric Signal Classification using a Finite Impulse Response Neural Network". Technical Report, The university of New Brunswork, Canada, June, 1994, pp. 803–820.
  7. Z. Fan and P. Mars, (1997) "Access flow control scheme for ATM networks using neural-network-based traffic prediction". Procedure for IEEE, Vol. 144, Dec. 5, October 1997, pp. 708– 714.
  8. G. Rama Marthy. (2008) "Finite Impulse Response FIR filter Model of Synapses: Associated Neural Network", Procedure of the Fourth Annual IEEE International Confidences on Natural Computation, 2008, pp. 3304–3309.
  9. G. Zichao and U. E. Robert. , (1992) "Using Genetic Algorithms to select input for Neural Network". Procedure of the IEEE International conference, May, 1992, pp. 87–95.
  10. K. J. Hintz. and J. J. Spofford , (1990) "Evoling Neural Network" Procedure of the IEEE Transactions on Communication and Intelligence, May 1990, pp. 333–338.
  11. S. Haykins, (2003), "Neural Networks – A comprehensive foundation", Prentice – Hall of India Private Limited, New-Delhi 2003.
  12. I. Ioan. , R. Corina and I. Arpad. , (2004) "The optimization of feed forward", procedure of the international and data – ICTAMI 2004, Thessalo-niki, Greece.
  13. I F. Emmonual C. and J. Barriel W. (2001) "Digital Signal Processing," A Practical Approch," Person Education (Singapore) Ltd. , 2001, Second Edition.
  14. J. Y. Dar. and C. F. Kun. , (2007) "Least square Design of FIR Filters based on a compacted Feedback inert Network", Proceeding of the IEEE Transaction on Circuits and systems, vol. 54 issue 5, May, 2007, pp. 427–431.
Index Terms

Computer Science
Information Sciences

Keywords

Window functions Artificial neural network.