Advertisement

Non-recursive FIR Band Pass Filter Optimization by Improved Particle Swarm Optimization

  • Sangeeta Mandal
  • Sakthi Prasad Ghoshal
  • Rajib Kar
  • Durbadal Mandal
  • S. Chaitnya Shiva
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 132)

Abstract

This paper proposes a novel optimal design of linear phase digital band pass finite impulse response (FIR) filter using Improved Particle Swarm Optimization (IPSO) technique. IPSO is an improved particle swarm optimization (PSO) that proposes a new definition for the velocity vector and swarm updating and hence the solution quality is improved. Evolutionary algorithms like real code genetic algorithm (RGA), PSO, IPSO have been used here for the design of linear phase band pass FIR filter. A comparison of simulation results reveals the optimization efficacy of the algorithm over the prevailing optimization techniques for the solution of the multimodal, non-differentiable, highly non-linear, and constrained filter design problems.

Keywords

Particle Swarm Optimization Finite Impulse Response Stop Band Finite Impulse Response Filter Real Code Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Mastorakis, N.E., Gonos, I.F., Swamy, M.N.S.: Design of Two Dimensional Recursive Filters Using Genetic Algorithms. IEEE Transaction on Circuits and Systems I - Fundamental Theory and Applications 50, 634–639 (2003)CrossRefMathSciNetGoogle Scholar
  2. 2.
    Ahmad, S.U., Antoniou, A.: A genetic algorithm approach for fractional delay FIR filters. In: IEEE International Symposium on Circuits and Systems, ISCAS 2006, pp. 2517–2520 (2006)Google Scholar
  3. 3.
    Lu, H.C., Tzeng, S.-T.: Design of arbitrary FIR log filters by genetic algorithm approach. Signal Processing 80, 497–505 (2000)CrossRefzbMATHGoogle Scholar
  4. 4.
    Chen, S.: IIR Model Identification Using Batch-Recursive Adaptive Simulated Annealing Algorithm. In: Proceedings of 6th Annual Chinese Automation and Computer Science Conference, pp. 151–155 (2000)Google Scholar
  5. 5.
    Karaboga, D., Horrocks, D.H., Karaboga, N., Kalinli, A.: Designing digital FIR filters using Tabu search algorithm. In: IEEE International Symposium on Circuits and Systems, ISCAS 1997, vol. 4, pp. 2236–2239 (1997)Google Scholar
  6. 6.
    Karaboga, N.: A new design method based on artificial bee colony algorithm for digital IIR filters. Journal of the Franklin Institute 346(4), 328–348 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
  7. 7.
    Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proc. IEEE Int. Conf. on Neural Network (1995)Google Scholar
  8. 8.
    Ababneh, J.I., Bataineh, M.H.: Linear phase FIR filter design using particle swarm optimization and genetic algorithms. Digital Signal Processing 18, 657–668 (2008)CrossRefGoogle Scholar
  9. 9.
    Biswal, B., Dash, P.K., Panigrahi, B.K.: Power quality disturbance classification using fuzzy C-means algorithm and adaptive particle swarm optimization. IEEE Trans. Ind. Electron. 56(1), 212–220 (2009)CrossRefGoogle Scholar
  10. 10.
    Parks, T.W., McClellan, J.H.: Chebyshev approximation for non recursive digital filters with linear phase. IEEE Trans. Circuits Theory CT-19, 189–194 (1972)Google Scholar
  11. 11.
    Luitel, B., Venayagamoorthy, G.K.: Differential Evolution Particle Swarm Optimization for Digital Filter Design. In: 2008 IEEE Congress on Evolutionary Computation (CEC 2008), pp. 3954–3961 (2008)Google Scholar
  12. 12.
    Sarangi, A., Mahapatra, R.K., Panigrahi, S.P.: DEPSO and PSO-QI in digital filter design. Expert Systems with Applications 38, 10966–10973 (2011)CrossRefGoogle Scholar
  13. 13.
    Mandal, D., Ghoshal, S.P., Bhattacharjee, A.K.: Application of Evolutionary Optimization Techniques for Finding the Optimal set of Concentric Circular Antenna Array. Expert Systems with Applications 38, 2942–2950 (2010)CrossRefGoogle Scholar
  14. 14.
    Mandal, D., Ghoshal, S.P., Bhattacharjee, A.K.: Swarm Intelligence Based Optimal Design of Concentric Circular Antenna Array. Journal of Electrical Engineering 10(3), 30–39 (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sangeeta Mandal
    • 1
  • Sakthi Prasad Ghoshal
    • 1
  • Rajib Kar
    • 2
  • Durbadal Mandal
    • 2
  • S. Chaitnya Shiva
    • 2
  1. 1.Department of Electrical Engg.National Institute of TechnologyDurgapurIndia
  2. 2.Department of Electronics and Communication EngineeringNational Institute of TechnologyDurgapurIndia

Personalised recommendations