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Design of Infinite Impulse Response Filter Using Fractional Derivative Constraints and Hybrid Particle Swarm Optimization | Circuits, Systems, and Signal Processing Skip to main content
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Design of Infinite Impulse Response Filter Using Fractional Derivative Constraints and Hybrid Particle Swarm Optimization

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Abstract

In this paper, a new method for designing digital infinite impulse response filter with nearly linear-phase response is presented using fractional derivative constraints (FDC). The design problem is constructed as a phase optimization problem between the desired and designed phase response of a filter. In order to achieve the highly accurate passband (pb) response, phase response is fitted to desired response more precisely using FDC, due to which design problem becomes a multimodal error surface that is constructed from sum of passband error (ep) and stopband error (es). Optimal value of FDC is accomplished by minimizing the total error (er0) using improved swarm-based optimization technique, which is formulated by associating the scout bee mechanism of artificial bee colony algorithm with particle swarm optimization and termed as hybrid particle swarm optimization. The simulated results reflect that the improved response in passband along with better transition width is achieved using the proposed method. It is observed that about 90–99% of improvement in passband error can be achieved with 100% reduction in maximum passband ripple. However, slight reduction in stopband attenuation (As), in some cases, results within the permissible limit. The designed filters using this method are also stable toward finite word length effect.

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References

  1. N. Agrawal, A. Kumar, V. Bajaj, Design of digital IIR filter with low quantization error using hybrid optimization technique. Soft Comput. 22(9), 2953–2971 (2018)

    Google Scholar 

  2. N. Agrawal, A. Kumar, V. Bajaj, A new design method for stable iir filters with nearly linear-phase response based on fractional derivative and swarm intelligence. IEEE Trans. Emerg. Top. Comput. Intell. 1(6), 464–477 (2017)

    Google Scholar 

  3. N. Agrawal, A. Kumar, V. Bajaj, Optimized design of digital IIR filter using artificial bee colony algorithm, in 3rd International Conference on Signal Processing, Computing and Control (ISPCC) (2015), pp. 316–321

  4. N. Agrawal, A. Kumar, V. Bajaj, G.K. Singh, Design of bandpass and bandstop infinite impulse response filters using fractional derivative. IEEE Trans. Ind. Electron. 66(2), 1285–1295 (2018)

    Google Scholar 

  5. N. Agrawal, A. Kumar, V. Bajaj, G.K. Singh, High order stable infinite impulse response filter design using cuckoo search algorithm. Int. J. Autom. Comput. 14(5), 589–602 (2017)

    Google Scholar 

  6. 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 Trans. Comput. Biol. Bioinf. 10(6), 1491–1504 (2013)

    Google Scholar 

  7. A. Antoniou, Digital Filters: Analysis, Design, and Applications, 2nd edn. (McGraw-Hill, New York, 2000)

    Google Scholar 

  8. K. Baderia, A. Kumar, G.K. Singh, Hybrid method for designing digital FIR filters based on fractional derivative constraints. ISA Trans. 58, 493–508 (2015)

    Google Scholar 

  9. J. Bai, X.C. Feng, Fractional-order anisotropic diffusion for image denoising. IEEE Trans. Image Process. 16(10), 2492–2502 (2007)

    MathSciNet  Google Scholar 

  10. L.W. Chen, Y.D. Jou, S.S. Hao, Design of two-channel quadrature mirror filter banks using minor component analysis algorithm. Circuits Syst. Signal Process. 34(5), 1549–1569 (2015)

    MathSciNet  Google Scholar 

  11. A. Chottera, G. Jullien, A linear programming approach to recursive digital filter design with linear phase. IEEE Trans. Circuits Syst. 29(3), 139–149 (1982)

    Google Scholar 

  12. 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 Process. 72(3), 193–198 (1999)

    MATH  Google Scholar 

  13. A. Jiang, H.K. Kwan, Minimax design of IIR digital filters using iterative SOCP. IEEE Trans. Circuits Syst. I Regul. Pap. 57(6), 1326–1337 (2010)

    MathSciNet  Google Scholar 

  14. A. Jiang, H.K. Kwan, IIR digital filter design with new stability constraint based on argument principle. IEEE Trans. Circuits Syst. I Regul. Pap. 56(3), 583–593 (2009)

    MathSciNet  Google Scholar 

  15. A. Jiang, H.K. Kwan, Minimax IIR digital filter design using SOCP, in IEEE International Symposium on Circuits and Systems (2008), pp. 2454–2457

  16. N. Karaboga, A new design method based on artificial bee colony algorithm for digital IIR filters. J. Frankl. Inst. 346(4), 328–348 (2009)

    MathSciNet  MATH  Google Scholar 

  17. N. Karaboga, B. Cetinkaya, Design of minimum phase digital IIR filters by using genetic algorithm. Signal Process. 16(1), 29–32 (2004)

    Google Scholar 

  18. S.S. Kidambi, Weighted least-squares design of recursive allpass filters. IEEE Trans. Signal Process. 44(6), 1553–1557 (1996)

    Google Scholar 

  19. B. Kuldeep, A. Kumar, G.K. Singh, Design of multi-channel cosine-modulated filter bank based on fractional derivative constraints using cuckoo search algorithm. Circuits Syst. Signal Process. 34(10), 3325–3351 (2015)

    Google Scholar 

  20. 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 Trans. 54, 101–116 (2015)

    Google Scholar 

  21. X. Lai, Z. Lin, Iterative reweighted minimax phase error designs of IIR digital filters with nearly linear phases. IEEE Trans. Signal Process. 64(9), 2416–2428 (2016)

    MathSciNet  MATH  Google Scholar 

  22. M.C. Lang, Least-squares design of IIR filters with prescribed magnitude and phase responses and a pole radius constraint. Signal Process. IEEE Trans. 48(11), 3109–3121 (2000)

    Google Scholar 

  23. Y.C. Lim, J.H. Lee, C.K. Chen, R.-H. Yang, A weighted least squares algorithm for quasi-equiripple FIR and IIR digital filter design. IEEE Trans. Signal Process. 40(3), 551–558 (1992)

    Google Scholar 

  24. W.S. Lu, Design of stable IIR digital filters with equiripple passbands and peak-constrained least-squares stopbands. IEEE Trans. Circuits Syst. II Analog Digit. Signal Process. 46(11), 1421–1426 (1999)

    Google Scholar 

  25. W.S. Lu, T. Hinamoto, Optimal design of IIR digital filters with robust stability using conic-quadratic programming updates. IEEE Trans. Signal Process. 51(6), 1581–1592 (2003)

    MathSciNet  MATH  Google Scholar 

  26. W.S. Lu, T. Hinamoto, Optimal design of IIR frequency-response-masking filters using second-order cone programming. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 50(11), 1401–1412 (2003)

    MathSciNet  MATH  Google Scholar 

  27. W.S. Lu, S.C. Pei, C.C. Tseng, A weighted least-squares method for the design of stable 1-D and 2-D IIR digital filters. IEEE Trans. Signal Process. 46(1), 1–10 (1998)

    Google Scholar 

  28. B. Luitel, G.K. Venayagamoorthy, Differential evolution particle swarm optimization for digital filter design, in IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) (2008), pp. 3954–3961

  29. T.Q. Nguyen, T.I. Laakso, R.D. Koilpillai, Eigenfilter approach for the design of allpass filters approximating a given phase response. IEEE Trans. Signal Process. 42(9), 2257–2263 (1994)

    Google Scholar 

  30. R.C. Nongpiur, D.J. Shpak, A. Antoniou, Improved design method for nearly linear-phase IIR filters using constrained optimization. IEEE Trans. Signal Process. 61(4), 895–906 (2013)

    MathSciNet  MATH  Google Scholar 

  31. K.B. Oldham, J. Spanier, The Fractional Calculus (Academic Press, New York, 1974)

    MATH  Google Scholar 

  32. S.T. Pan, Evolutionary computation on programmable robust IIR filter pole-placement design. IEEE Trans. Instrum. Meas. 60(4), 1469–1479 (2011)

    Google Scholar 

  33. D. Pelusi, R. Mascella, L. Tallini, A fuzzy gravitational search algorithm to design optimal IIR filters. Energies 11(4), 736 (2018)

    Google Scholar 

  34. Y.F. Pu, J.L. Zhou, X. Yuan, Fractional differential mask: a fractional differential-based approach for multiscale texture enhancement. IEEE Trans. Image Process. 19(2), 491–511 (2010)

    MathSciNet  MATH  Google Scholar 

  35. L. Rabiner, N. Graham, H. Helms, Linear programming design of IIR digital filters with arbitrary magnitude function. IEEE Trans. Acoust. 22(2), 117–123 (1974)

    Google Scholar 

  36. S.M. Rafi, A. Kumar, G.K. Singh, An improved particle swarm optimization method for multirate filter bank design. J. Frankl. Inst. 350(4), 757–769 (2013)

    MathSciNet  MATH  Google Scholar 

  37. S.K. Saha, R. Kar, D. Mandal, S.P. Ghoshal, An efficient craziness based particle swarm optimization technique for optimal IIR filter design, in Transactions on Computational Science, ed. by M.L. Gavrilova, C.J.K. Tan, M.L. Gavrilova, C.J.K. Tan (Springer, New York, 2013), pp. 230–252

    Google Scholar 

  38. I.W. Selesnick, Low-pass filters realizable as all-pass sums: design via a new flat delay filter. IEEE Trans. Circuits Syst. II Analog Digit. Signal Process. 46(1), 40–50 (1999)

    Google Scholar 

  39. I. Sharma, A. Kumar, G.K. Singh, An efficient method for designing multiplier-less non-uniform filter bank based on hybrid method using cse technique. Circuits Syst. Signal Process. 36(3), 1169–1191 (2017)

    Google Scholar 

  40. J.L. Sullivan, J.W. Adams, PCLS IIR digital filters with simultaneous frequency response magnitude and group delay specifications. IEEE Trans. Signal Process. 46(11), 2853–2861 (1998)

    Google Scholar 

  41. K.S. Tang, K.F. Man, S. Kwong, Z.F. Liu, Design and optimization of IIR filter structure using hierarchical genetic algorithms. IEEE Trans. Ind. Electron. 45(3), 481–487 (1998)

    Google Scholar 

  42. C.C. Tseng, Design of variable and adaptive fractional order FIR differentiators. Signal Process. 86(10), 2554–2566 (2006)

    MATH  Google Scholar 

  43. C.C. Tseng, Design of fractional order digital FIR differentiators. IEEE Signal Process. Lett. 8(3), 77–79 (2001)

    Google Scholar 

  44. C.C. Tseng, S.L. Lee, Design of linear phase FIR filters using fractional derivative constraints. Signal Process. 92(5), 1317–1327 (2012)

    Google Scholar 

  45. C.C. Tseng, S.L. Lee, Design of wideband fractional delay filters using derivative sampling method. IEEE Trans. Circuits Syst. 57(8), 2087–2098 (2010)

    MathSciNet  Google Scholar 

  46. C.C. Tseng, S.C. Pei, Stable IIR notch filter design with optimal pole placement. IEEE Trans. Signal Process. 49(11), 2673–2681 (2001)

    MathSciNet  MATH  Google Scholar 

  47. Y. Yu, Y. Xinjie, Cooperative coevolutionary genetic algorithm for digital IIR filter design”. IEEE Trans. Ind. Electron. 54(3), 1311–1318 (2007)

    Google Scholar 

  48. X. Zhang, H. Iwakura, Design of IIR digital allpass filters based on eigenvalue problem. IEEE Trans. Signal Process. 47(2), 554–559 (1999)

    Google Scholar 

Download references

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Agrawal, N., Kumar, A. & Bajaj, V. Design of Infinite Impulse Response Filter Using Fractional Derivative Constraints and Hybrid Particle Swarm Optimization. Circuits Syst Signal Process 39, 6162–6190 (2020). https://doi.org/10.1007/s00034-020-01456-0

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