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Design of Digital IIR Filters using Integrated Cat Swarm Optimization and Differential Evolution

by Kamalpreet Kaur, J. S. Dhillon
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 99 - Number 4
Year of Publication: 2014
Authors: Kamalpreet Kaur, J. S. Dhillon
10.5120/17362-7876

Kamalpreet Kaur, J. S. Dhillon . Design of Digital IIR Filters using Integrated Cat Swarm Optimization and Differential Evolution. International Journal of Computer Applications. 99, 4 ( August 2014), 28-43. DOI=10.5120/17362-7876

@article{ 10.5120/17362-7876,
author = { Kamalpreet Kaur, J. S. Dhillon },
title = { Design of Digital IIR Filters using Integrated Cat Swarm Optimization and Differential Evolution },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 99 },
number = { 4 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 28-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume99/number4/17362-7876/ },
doi = { 10.5120/17362-7876 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:27:19.821417+05:30
%A Kamalpreet Kaur
%A J. S. Dhillon
%T Design of Digital IIR Filters using Integrated Cat Swarm Optimization and Differential Evolution
%J International Journal of Computer Applications
%@ 0975-8887
%V 99
%N 4
%P 28-43
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper aims to establish a solution methodology for the optimal design of digital infinite impulse response (IIR) filters by integrating the features of cat swarm optimization (CSO) and differential evolution algorithm (DE). DE is a population based stochastic optimization technique which optimizes real valued functions. It requires negligible control parameter tuning but sometimes causes instability problem. CSO is a heuristic optimization algorithm based on the observations and imitation of the natural behavior of cats. CSO algorithm possesses local as well as global search capabilities. Although, CSO possesses better capability to search optimal point but it requires a higher computation time because the local and global searches are carried out independently in each iteration. A hybrid algorithm is proposed using the CSO algorithm and the DE optimization algorithm for the robust and stable design of digital IIR filter. To start with a better solution set, opposition based learning strategy is incorporated. The proposed method explores and exploits the search space locally as well as globally. The design criterion undertakes the minimization of magnitude approximation error and ripple magnitudes of both pass-band and stop-band satisfying the stability requirements. The developed hybrid algorithm is effectively applied for designing the digital low-pass, high-pass, band-pass and band-stop filters. The computational results demonstrate that the proposed algorithm is capable of creating designs that are competitive with reference to other design processes and can efficiently be applied for higher order filter design.

References
  1. I. Jury, Theory and Application of the Z-Transform Method, New York: Wiley, 1964.
  2. S. K. Mitra and J. F. Kaiser, Handbook for Digital Signal Processing, Wiley, New York, 1993.
  3. J. Kennedy and R. Eberhart, "Particle Swarm Optimization," IEEE International Conference on Neural Networks, Piscataway, New Jersey, U. S. A, vol. 4, pp. 1942-1948, 1995.
  4. R. Storm and K. Prince, "Differential evolution-A Simple and Efficient Heurist for Global Optimization over Continuous Spaces," University of California, Berkeley, International Computational Sciences Institute, Berkeley, March 1995.
  5. J. H. Li and F. L. Yin, "Genetic Optimization Algorithm for Designing IIR Digital Filters," Journal of China Institute of Communications, vol. 17, pp. 1–7, 1996.
  6. J. M. Renders and S. P. Flasse, "Hybrid Methods Using Genetic Algorithms for Global Optimization," IEEE Transactions on Systems, Man, and Cybernetics-Part B, vol. 26, no. 2, pp. 243-258, April 1996.
  7. K. S. Tang, K. F. Man, S. Kwong and Z. F. Liu, "Design and Optimization of IIR Filter Structure using Hierarchical Genetic Algorithms," IEEE Transaction on Industrial Electronics, vol. 45, no. 3, pp. 481–487, June 1998.
  8. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, Wiley, New York, 2001.
  9. A. Silva, A. Neves and E. Costa, "An Empirical comparison of Particle Swarm and Predator Prey Optimization," Proceedings of Irish International Conference on Artificial Intelligence and Cognitive Science, vol. 24, no. 64, pp 103-110, 2002.
  10. Y. S. Ong and A. J. Keane, "A Domain Knowledge based Search Advisor for Design Problem solving environments," Engineering Application and Artificial Intelligence, vol. 15, no. 1, pp. 105–116, 2002.
  11. E. C. Ifeachor and B. W. Jervis, Digital signal processing, a practical approach, 2nd edition, Pearson Education, Singapore, 2003.
  12. N. Karaboga, A. Kalinli, and D. Karaboga, "Designing IIR Filters using Ant Colony Optimization Algorithm," Journal of Engineering Applications of Artificial Intelligence, vol. 17, no. 3, pp. 301–309, April 2004.
  13. A. Kalinli and N. Karaboga, "A New Method for Adaptive IIR Filter Design Based On Tabu Search Algorithm," International Journal of Electronics and Communication (AEÜ), vol. 59, no. 2, pp. 111–117, 2005.
  14. X. Li, "Ef?cient Differential Evolution using Speciation for Multimodal Function Optimization," Proceedings of International Conference on Evolutionary Computation, , pp. 873–880, 2005.
  15. Y. S. Ong, M. H. Lim, N. Zhu, and K. W. Wong, "Classi?cation of Adaptive Memetic Algorithms: A comparative study," IEEE Transaction on System Man and Cybernatics Part B: Cybernatics, vol. 36, no. 1, pp. 141–152, Feb. 2006.
  16. Jinn-Tsong Tsai, Jyh-Horng Chou and Tung-Kuan Liu, "Optimal Design of Digital IIR filters by using Hybrid Taguchi Genetic Algorithm," IEEE Transactions on Industrial Electronics, vol. 53, no. 3, pp. 867–879, June 2006.
  17. Jinn-Tsong Tsai and Jyh-Horng, "Optimal Design of Digital IIR Filters using an Improved Immune Algorithm," IEEE transactions on Signal Processing, vol. 54, no. 12, pp. 4582–4596, December 2006.
  18. S. C. Chu and P. W. Tsai, "Computational Intelligence based on the Behavior of Cat," International Journal of Innovative computing, Information and Control, vol. 3, no. 1, pp. 163-173, 2007.
  19. Y. Yu and Y. Xinjie, "Cooperative co-evolutionary Genetic Algorithm for Digital IIR Filter Design," IEEE Transactions on Industrial Electronics, vol. 54, no. 3, pp. 1311–1318, June 2007.
  20. Rahnamayan, H. R. Tizhoosh and M. A. Salama, "Opposition based Differential Evolution," IEEE Transactions on Evolutionary Computations, vol. 12, no. 1, pp 64-79, February 2008.
  21. V. Y Del, G. K. Venayagamoorthy, S. Mohagheghi, J. C. G. Hernandez and R. Harely, "Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems," IEEE Transactions on Evolutionary Computation, vol. 12, no. 2, pp 171-195, 2008.
  22. N. Noman and H. Iba, "Accelerating Differential Evolution Using an Adaptive Local Search," IEEE Transactions on Evolutionary Computation, vol. 12, no 1, pp 107-125, February 2008.
  23. Sum-Im, G. A. Taylor, M. R. Irving and Y. H. Song, "Differential Evolution Algorithm for Static Multistage Transmission Expansion Planning," IET Generation, Transmission and Distribution, vol. 3, no. 4, pp 365-384, 2009.
  24. Aimin Jiang and Hon Keung Kwan, "IIR Digital Filter Design with New Stability Constraint based on Argument Principle," IEEE Transactions on Circuit and Systems-I, vol. 56, no. 3, pp. 583–593, March 2009.
  25. A. K. Qin, V. L. Huang and P. N. Sugathan, "Differential Evaluation Algorithm With Strategy Adapter for Global Numerical Optimization," IEEE Transactions on Evolutionary Computation, vol. 13, no. 2,pp 398-417, April 2009.
  26. S. Chattopadhyay, S. K. Sanyal and A. Chandra, "Design of FIR Filter using Differential Evolution Optimization and is Effect as a Pulse Shaping Filter In a QPSK Modulated System," International Journal of Computer Science and Network Security, vol. 10, no. 1, pp. 313-321, January 2010.
  27. D. Chaohua , W. Chen and Y. Zhu, "Seeker Optimization Algorithm for Digital IIR Filter Design," IEEE Transactions on Industrial Electronics, vol. 57, no. 5, pp. 1710-1718, May 2010.
  28. Proakis, J. G. , Digital signal processing, Prentice-Hall International. Inc. , New Jersey, (2010).
  29. S. Das and P. N. Suganthan, "Differential Evolution: A Survey of the State-of-the-Art, "IEEE Transactions on Evolutionary Computation," vol. 15, no. 1, pp. 4-31, February 2011.
  30. G. Panda, P. M. Pradhan and B. Majhi, "IIR System Identification Using Cat Swarm Optimization," Expert Systems with Applications, vol. 38, no. 10, pp. 12671-12683, September 2011.
  31. D. P. Kothari and J. S. Dhillon, Power system Optimization, Prentice Hall of India, 2nd Edition, New Delhi, (2011).
  32. R. Kaur, M. S. Patterh, J. S. Dhillon, "Design of Optimal L1 Stable IIR Digital Filter using Hybrid Optimization Algorithm," International Journal of Computer Applications, vol. 38, no 2 ,pp 27-32, January 2012.
  33. Pei-Wei Tsai, Jeng-Shyang Pan, Shyi-Ming Chen and Bin-Yih Lio, "Enhanced Parallel Cat Swarm Optimization based on the Taguchi method," Expert Systems with Applications, vol. 39, no. 10, pp. 6309-6319, 2012.
  34. B. Singh, J. S Dhillon, Y. S. Brar, "Design of Digital IIR filter: A Comparison," International journal of Electrical, Electronics and Telecommunication Engineering, vol. 44, no. 1, pp. 1108-1121, February 2012.
  35. P. M. Mohan and G. Panda, "Solving Multiobjective Problems using Cat Swarm Optimization," Expert Systems with Applications, vol. 39, no. 10, pp. 2956-2964, 2012.
  36. R. Kaur, M. S Patterh, J. S Dhillon and D. Singh, "Heuristic search method for digital IIR filters design," Wseas Transactions on Signal Processing, vol. 8, pp. 121-134, July 2012.
  37. Zhi-Hui Wang, Chin-Chen Chang and Ming-Chu Li, "Optimizing Least-Significant-Bit Substitution using Cat Swarm Optimization Strategy," Information Sciences, vol. 192, no. , pp. 98-108, 2012.
  38. B. Singh, J. S Dhillon and Y. S. Brar, "A Hybrid Differential Evolution Method for the Design of IIR Digital Filter," International Journal on Signal and Image Processing, vol. 4, no. 1, pp. 1-10, January 2013.
  39. R. Kaur, M. S Patterh and J. S Dhillon, "Real Coded Genetic Algorithm for Design of IIR Digital Filter with Conflicting Objectives," International Journal of Applied Mathematics and Information Sciences, vol. 8, no. 5, pp. 2635-2644, 2014.
Index Terms

Computer Science
Information Sciences

Keywords

Digital IIR filters cat swarm optimization differential evolution multiparameter optimization opposition based learning.

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