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Link to original content: https://doi.org/10.1007/s11633-017-1091-x
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High order stable infinite impulse response filter design using cuckoo search algorithm

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Abstract

In this paper, an efficient technique for optimal design of digital infinite impulse response (IIR) filter with minimum passband error (e p ), minimum stopband error (e s ), high stopband attenuation (A s ), and also free from limit cycle effect is proposed using cuckoo search (CS) algorithm. In the proposed method, error function, which is multi-model and non-differentiable in the heuristic surface, is constructed as the mean squared difference between the designed and desired response in frequency domain, and is optimized using CS algorithm. Computational efficiency of the proposed technique for exploration in search space is examined, and during exploration, stability of filter is maintained by considering lattice representation of the denominator polynomials, which requires less computational complexity as well as it improves the exploration ability in search space for designing higher filter taps. A comparative study of the proposed method with other algorithms is made, and the obtained results show that 90% reduction in errors is achieved using the proposed method. However, computational complexity in term of CPU time is increased as compared to other existing algorithms.

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References

  1. N. Karaboga, F. Latifoglu. Elimination of noise on transcranial Doppler signal using IIR filters designed with artificial bee colony-ABC-algorithm. Digital Signal Processing, vol. 23, no. 3, pp. 1051–1058, 2013.

    Article  MathSciNet  Google Scholar 

  2. A. Hartmann, J. M. Lemos, R. S. Costa, S. Vinga. Identifying IIR filter coefficients using particle swarm optimization with application to reconstruction of missing cardiovascular signals. Engineering Applications of Artificial Intelligence, vol. 34, pp. 193–198, 2014.

    Article  Google Scholar 

  3. L. Eriksson, M. Allie, R. Greiner. The selection and application of an IIR adaptive filter for use in active sound attenuation. IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 35, no. 4, pp. 433–437, 1987.

    Article  Google Scholar 

  4. A. Gotmare, R. Patidar, N. V. George. Nonlinear system identification using a cuckoo search optimized adaptive Hammerstein model. Expert Systems with Applications, vol. 42, no. 5, pp. 2538–2546, 2015.

    Article  Google Scholar 

  5. M. C. Lang. Least-squares design of IIR filters with prescribed magnitude and phase responses and a pole radius constraint. IEEE Transactions on Signal Processing, vol. 48, no. 11, pp. 3109–3121, 2000.

    Article  Google Scholar 

  6. A. M. Jiang, H. K. Kwan. Minimax design of IIR digital filters using iterative SOCP. IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 57, no. 6, pp. 1326–1337, 2010.

    Article  MathSciNet  Google Scholar 

  7. A.M. Jiang, H. K. Kwan. Minimax IIR digital filter design using SOCP. In Proceedings of International Symposium on Circuits and Systems, IEEE, Seattle, USA, pp. 2454–2457, 2008.

    Google Scholar 

  8. K. S. Tang, K. F. Man, S. Kwong, Z. F. Liu. Design and optimization of IIR filter structure using hierarchical genetic algorithms. IEEE Transactions on Industrial Electronics, vol. 45, no. 3, pp. 481–487, 1998.

    Article  Google Scholar 

  9. Y. Yang, X. J. Yu. Cooperative coevolutionary genetic algorithm for digital IIR filter design. IEEE Transactions on Industrial Electronics, vol. 54, no. 3, pp. 1311–1318, 2007.

    Article  Google Scholar 

  10. J. Chen, F. Pan, T. Cai. Acceleration factor harmonious particle swarm optimizer. International Journal of Automation and Computing, vol. 3, no. 1, pp. 41–46, 2006.

    Article  Google Scholar 

  11. G. H. Lin, J. Zhang, Z. H. Liu. Hybrid particle swarm optimization with differential evolution for numerical and engineering optimization. International Journal of Automation and Computing, [Online], Available: http://link.springer.com/article/10.1007/s11633-016- 0990-6, 2017.

    Google Scholar 

  12. M. K. Ahirwal, A. Kumar, G. K. Singh. Adaptive filtering of EEG/ERP through noise cancellers using an improved PSO algorithm. Swarm and Evolutionary Computation, vol. 14, pp. 76–91, 2014.

    Article  Google Scholar 

  13. M. K. Ahirwal, A. Kumar, G. K. Singh. EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms. IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 6, pp. 1491–1504, 2013.

    Article  Google Scholar 

  14. A. K. Bhandari, V. K. Singh, A. Kumar, G. K. Singh. Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur’s entropy. Expert Systems with Applications, vol. 41, no. 7, pp. 3538–3560, 2014.

    Article  Google Scholar 

  15. A. K. Bhandari, V. Soni, A. Kumar, G. K. Singh. Cuckoo search algorithm based satellite image contrast and brightness enhancement using DWT-SVD. ISA Transactions, vol. 53, no. 4, pp. 1286–1296, 2014.

    Article  Google Scholar 

  16. B. Kuldeep, V. K. Singh, A. Kumar, G. K. Singh. Design of two-channel filter bank using nature inspired optimization based fractional derivative constraints. ISA Transactions, vol. 54, pp. 101–116, 2015.

    Article  Google Scholar 

  17. K. Baderia, A. Kumar, G. K. Singh. Hybrid method for designing digital FIR filters based on fractional derivative constraints. ISA Transactions, vol. 58, pp. 493–508, 2015.

    Article  Google Scholar 

  18. B. Kuldeep, A. Kumar, G. K. Singh. Design of multichannel cosine-modulated filter bank based on fractional derivative constraints using cuckoo search algorithm. Circuits, Systems, and Signal Processing, vol. 34, no. 10, pp. 3325–3351, 2015.

    Article  Google Scholar 

  19. L. L. Li, D. H. Zhou, L. Wang. Fault diagnosis of nonlinear systems based on hybrid PSOSA optimization algorithm. International Journal of Automation and Computing, vol.4, no. 2, pp. 183–188, 2007.

    Article  Google Scholar 

  20. A. Lee, M. Ahmadi, G. A. Jullien, W. C. Miller, R. S. Lashkari. Digital filter design using genetic algorithm. In Proceedings of Symposium on Advances in Digital Filtering and Signal Processing, IEEE, Victoria, Canada, pp. 34–38, 1998.

    Google Scholar 

  21. I. Sharma, A. Kumar, G. K. Singh. Adjustable window based design of multiplier-less cosine modulated filter bank using swarm optimization algorithms. AEU-International Journal of Electronics and Communications, vol. 70, no. 1, pp. 85–94, 2016.

    Article  Google Scholar 

  22. I. Sharma, B. Kuldeep, A. Kumar, V. K. Singh. Performance of swarm based optimization techniques for designing digital FIR filter: A comparative study. Engineering Science and Technology, an International Journal, vol. 19, no. 3, pp. 1564–1572, 2016.

    Article  Google Scholar 

  23. A. Shirvani, K. Khezri, F. Razzazi, C. Lucas. Designing linear phase fir filters with particle swarm optimization and harmony search. In Proceedings of International Conference on Signal and Image Processing, Jeju Island, Korea, pp. 193–200, 2009.

    Google Scholar 

  24. N. Karaboga, B. Cetinkaya. Design of minimum phase digital IIR filters by using genetic algorithm. In Proceedings of the 6th Nordic Signal Processing Symposium, IEEE, Espoo, Finland, pp. 29–32, 2004.

    Google Scholar 

  25. S. K. Saha, R. Kar, D. Mandal, S. P. Ghoshal. Bacteria foraging optimisation algorithm for optimal FIR filter design. International Journal of Bio-Inspired Computation, vol.5, no. 1, pp. 52–66, 2013.

    Article  Google Scholar 

  26. S. Chen, R. H. Istepanian, B. L. Luk. Signal processing applications using adaptive simulated annealing. In Proceedings of Congress on Evolutionary Computation, IEEE, Washington DC, USA, vol. 2, pp. 842–849, 1999.

    Google Scholar 

  27. C. Sheng, L. L. Bing. Digital IIR filter design using particle swarm optimisation. International Journal of Modelling, Identification and Control, vol. 9, no. 4, pp. 327–335, 2010.

    Article  Google Scholar 

  28. X. Li, R. C. Zhao, Q. Wang. Optimizing the design of IIR filter via genetic algorithm. In Proceedings of International Conference on Neural Networks and Signal Processing, IEEE, Nanjing, China, vol. 1, pp. 476–479, 2003.

    Google Scholar 

  29. J. T. Tsai, J. H. Chou, T. K. 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, 2006.

    Article  Google Scholar 

  30. S. K. Saha, R. Kar, D. Mandal, S. P. Ghoshal. An efficient craziness based particle swarm optimization technique for optimal IIR filter design. Transactions on Computational Science XXI, M. L. Gavrilova, C. J. K. Tan, A. Abraham, Eds., Berlin Heidelberg, Germany: Springer, pp. 230–252, 2013.

    Chapter  Google Scholar 

  31. X. Z. Zhang, P. G. Jia, J. Y. Guo. An improved particle swarm optimizer for IIR digital filter design. In Proceedings of International Conference on Intelligent Systems and Knowledge Engineering, IEEE, Hangzhou, China, pp. 191–196, 2010.

    Google Scholar 

  32. S. M. Rafi, A. Kumar, G. K. Singh. An improved particle swarm optimization method for multirate filter bank design. Journal of the Franklin Institute, vol. 350, no. 4, pp. 757–769, 2013.

    Article  MathSciNet  MATH  Google Scholar 

  33. N. Agrawal, A. Kumar, V. Bajaj. Hybrid method based optimized design of digital IIR filter. In Proceedings International Conference on Communications and Signal Processing, IEEE, Melmaruvathur, India, pp. 1549–1554, 2015.

    Google Scholar 

  34. C. H. Dai, W. R. Chen, Y. F. Zhu. Seeker optimization algorithm for digital IIR filter design. IEEE Transactions on Industrial Electronics, vol. 57, no. 5, pp. 1710–1718, 2010.

    Article  Google Scholar 

  35. Y. Wang, B. Li, T. Weise. Two-stage ensemble memetic algorithm: Function optimization and digital IIR filter design. Information Sciences, vol. 220, pp. 408–424, 2013.

    Article  Google Scholar 

  36. C.W. Tsai, C. H. Huang, C. L. Lin. Structure specified IIR filter and control design using real structured genetic algorithm. Applied Soft Computing, vol. 9, no. 4, pp. 1285–1295, 2009.

    Article  Google Scholar 

  37. B. Li, Y. Wang, T. Weise, L. Long. Fixed-point digital IIR filter design using two-stage ensemble evolutionary algorithm. Applied Soft Computing, vol. 13, no. 1, pp. 329–338, 2013.

    Article  Google Scholar 

  38. X. S. Yang, S. Deb. Cuckoo Search via Lévy flights. In Proceedings of World Congress on Nature & Biologically Inspired Computing, IEEE, Coimbatore, India, pp. 210–214, 2009.

    Google Scholar 

  39. X. S. Yang. Cuckoo search and firefly algorithm: Overview and analysis. Cuckoo Search and Firefly Algorithm: Theory and Applications, X. S. Yang, Ed., Switzerland: Springer International Publishing, pp. 1–26, 2014.

    Chapter  Google Scholar 

  40. M. Kumar, T. K. Rawat. Optimal fractional delay-IIR filter design using cuckoo search algorithm. ISA Transactions, vol. 59, pp. 39–54, 2015.

    Article  Google Scholar 

  41. A. P. Patwardhan, R. Patidar, N. V. George. On a cuckoo search optimization approach towards feedback system identification. Digital Signal Processing, vol. 32, pp. 156–163, 2014.

    Article  Google Scholar 

  42. F. Wysocka-Schillak. Approximation of FIR by IIR filters using hybrid genetic algorithm. In Proceedings of Signal Processing Algorithms, Architectures, Arrangements, and Applications, IEEE, Poznan, Poland, pp. 149–154, 2008.

    Google Scholar 

  43. S. T. Pan. Evolutionary computation on programmable robust IIR filter pole-placement design. IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 4, pp. 1469–1479, 2011.

    Article  Google Scholar 

  44. M. K. Ahirwal, A. Kumar, G. K. Singh. Adaptive filtering of EEG/ERP through Bounded Range Artificial Bee Colony (BR-ABC) algorithm. Digital Signal Processing, vol. 25, pp. 164–172, 2014.

    Article  Google Scholar 

  45. A. Sarangi, S. K. Sarangi, S. K. Padhy, S. P. Panigrahi, B. K. Panigrahi. Swarm intelligence based techniques for digital filter design. Applied Soft Computing, vol. 25, pp. 530–534, 2014.

    Article  Google Scholar 

  46. X. S. Yang, S. Deb. Multiobjective cuckoo search for design optimization. Computers & Operations Research, vol. 40, no. 6, pp. 1616–1624, 2013.

    Article  MathSciNet  MATH  Google Scholar 

  47. J. G. Proakis, D. G. Manolakis. Design of digital filters. Digital Signal Processing, 3rd ed., New Jersey, USA: Prentice Hall, pp. 666–692, 1996.

    Google Scholar 

  48. S. K. Saha, S. Sarkar, R. Kar, D. Mandal, S. P. Ghoshal. Digital stable IIR low pass filter optimization using particle swarm optimization with improved inertia weight. In Proceedings of the 9th International Joint Conference on Computer Science and Software Engineering, IEEE, Bangkok, Thailand, pp. 147–152, 2012.

    Google Scholar 

  49. M. K. Ahirwal, A. Kumar, G. K. Singh. Analysis and testing of PSO variants through application in EEG/ERP adaptive filtering approach. Biomedical Engineering Letters, vol. 2, no. 3, pp. 186–197, 2012.

    Article  Google Scholar 

  50. A. Djebbari, J. M. Rouvaen, A. L. Djebbari, M. F. Belbachir, S. A. Elahmar. A new approach to the design of limit cycle-free IIR digital filters using eigenfilter method. Signal Processing, vol. 72, no. 3, pp. 193–198, 1999.

    Article  MATH  Google Scholar 

  51. S. K. Saha, R. Kar, D. Mandal, S. P. Ghoshal. Gravitation search algorithm: Application to the optimal IIR filter design. Journal of King Saud University-Engineering Sciences, vol. 26, no. 1, pp. 69–81, 2014.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, the Pandit Dwarka Prasad Mishra, Indian Institute of Information Technology, Design and Manufacturing, Dumna, 482005, India

    N. Agrawal, A. Kumar & V. Bajaj

  2. School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, Korea

    A. Kumar

  3. Department of Electrical Engineering, Indian Institute of Technology, Roorkee, 247667, India

    G. K. Singh

Authors
  1. N. Agrawal
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  2. A. Kumar
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  3. V. Bajaj
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  4. G. K. Singh
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Corresponding author

Correspondence to N. Agrawal.

Additional information

Recommended by Associate Editor Victor Becerra

N. Agrawal received B. Eng. degree in electronic and communication engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya, India in 2010. Currently, he is a Ph. D. degree candidate in the Electronic and Communication Engineering Department at Indian Institute of Information Technology, Design and Manufacturing, India.

His research interests include designing of optimal filter, optimization techniques and embedded system design for signal processing.

A. Kumar received the B. Eng. degree in electronic and telecommunication engineering from the Army Institute of Technology (AIT), Pune University, India in 2002, and received the M.Tech. and Ph.D. degrees in electronic and telecommunication engineering from Indian Institute of Technology (IIT) Roorkee, India in 2006, and 2010, respectively. He is an assistant professor in Electronic and Communication Engineering Department, Pandit Dwarka Prasad Mishra Indian Institute of Information Technology, Design & Manufacturing, India. Currently, he is a visiting researcher at School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Korea.

His research interests include design of digital filters and multirate filter bank, multirate signal processing, biomedical signal processing, image processing, and speech processing.

V. Bajaj received the B.Eng. degree in electronics and communication engineering from Rajiv Gandhi Technological University, India in 2006. He received the M.Tech. (Hons.) degree in microelectronics and very-large-scale integration (VLSI) design from Shri Govindram Seksaria Institute of Technology and Science, India in 2009. He received the Ph.D. degree in the Discipline of Electrical Engineering, at Indian Institute of Technology Indore, India. Presently, he is working as assistant professor with the Discipline of Electronics and Communication Engineering, Indian Institute of Information Technology, Design and Manufacturing Jabalpur, India.

His research interests include biomedical signal processing, image processing and time-frequency analysis.

G. K. Singh received the B.Tech. degree from the Govind Ballabh Pant University of Agriculture and Technology, India in 1981, and the Ph.D. degree from Banaras Hindu University, India in 1991, both in electrical engineering. He worked in the industry for nearly five and a half years. Currently, he is a professor in the Electrical Engineering Department, IIT Roorkee, India. He has coordinated a number of research projects sponsored by the Council of Scientific & Industrial Research (CSIR) and University Grants Commission (UGC), Government of India.

His research interests include design and analysis of electrical machines and biomedical signal processing.

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Agrawal, N., Kumar, A., Bajaj, V. et al. High order stable infinite impulse response filter design using cuckoo search algorithm. Int. J. Autom. Comput. 14, 589–602 (2017). https://doi.org/10.1007/s11633-017-1091-x

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