Optimal Linear Phase Finite Impulse Response Band Pass   Filter Design Using Craziness
Based Particle Swarm   Optimization Algorithm

doi:10.1007/s12204-011-1213-5

Abstract

Abstract: An efficient method is proposed for the
design of finite impulse response (FIR) filter with arbitrary pass
band edge, stop band edge frequencies and transition width. The
proposed FIR band stop filter is designed using craziness based
particle swarm optimization (CRPSO) approach. Given the filter
specifications to be realized, the CRPSO algorithm generates a set
of optimal filter coefficients and tries to meet the ideal frequency
response characteristics. In this paper, for the given problem, the
realizations of the optimal FIR band pass filters of different
orders have been performed. The simulation results have been
compared with those obtained by the well accepted evolutionary
algorithms, such as Parks and McClellan algorithm (PMA), genetic
algorithm (GA) and classical particle swarm optimization (PSO).
Several numerical design examples justify that the proposed optimal
filter design approach using CRPSO outperforms PMA and PSO, not only
in the accuracy of the designed filter but also in the convergence
speed and solution quality.

Key words:

摘要： An efficient method is proposed for the
design of finite impulse response (FIR) filter with arbitrary pass
band edge, stop band edge frequencies and transition width. The
proposed FIR band stop filter is designed using craziness based
particle swarm optimization (CRPSO) approach. Given the filter
specifications to be realized, the CRPSO algorithm generates a set
of optimal filter coefficients and tries to meet the ideal frequency
response characteristics. In this paper, for the given problem, the
realizations of the optimal FIR band pass filters of different
orders have been performed. The simulation results have been
compared with those obtained by the well accepted evolutionary
algorithms, such as Parks and McClellan algorithm (PMA), genetic
algorithm (GA) and classical particle swarm optimization (PSO).
Several numerical design examples justify that the proposed optimal
filter design approach using CRPSO outperforms PMA and PSO, not only
in the accuracy of the designed filter but also in the convergence
speed and solution quality.

关键词:

CLC Number:

TN713

SANGEETA Mandal, SAKTI Prasad Ghoshal, RAJIB Kar, . Optimal Linear Phase Finite Impulse Response Band Pass Filter Design Using Craziness
Based Particle Swarm Optimization Algorithm[J]. Journal of shanghai Jiaotong University (Science), 2011, 16(6): 696-703.

References

[1] Litwin L. FIR and IIR digital filters [J].   IEEE Potentials, 2000, 19 (4): 28-31.

    [2] Parks T W, Burrus C S. Digital filter design [M]. New York: Wiley, 1987.

    [3] Parks T W, Mcclellan J H. Chebyshev approximation for non recursive

digital filters with linear phase [J].   IEEE Transactions on

Circuits Theory, 1972, 19 (2): 189-194.

    [4] Mcclellan J H, Parks T W, Rabiner L R. A computer program for designing

optimum FIR linear phase digital filters [J].   IEEE

Transactions on Audio Electroacoustics, 1973, 21 (6): 506-526.

    [5] Rabiner L R. Approximate design relationships for low-pass FIR digital

filters [J].   IEEE Transactions on Audio Electroacoustics ,

1973, 21 (6): 456-460.

    [6] Lin Z. An introduction to time-frequency signal analysis [J].   Sensor Review ,

1997, 17 (1): 46-53.

    [7] Chen S. IIR model identification using batch-recursive adaptive

simulated annealing algorithm [C]//   Proceedings of 6th Annual

Chinese Automation and Computer Science Conference. Loughborough,

UK: [s.n.], 2000: 151-155.

    [8] Mastorakis N E, Gonos I F, Swamy M N S. Design of two dimensional

recursive filters using genetic algorithms [J].   IEEE

Transaction on Circuits and Systems. I: Fundamental Theory and

Applications, 2003, 50 (5): 634-639.

    [9] Karaboga N. A new design method based on artificial bee colony algorithm

for digital IIR filters [J],   Journal of the Franklin

Institute, 2009, 346 (4): 328-348.

    [10] Kennedy J, Eberhart R. Particle swarm optimization [C]// Proceedings of IEEE International Conference on Neural Network. Perth,

Australia: IEEE, 1995: 1942-1948.

    [11] Eberhart R C, Shi Y. Comparison between genetic algorithms and particle

swarm optimization [J].    Lecture   Notes in Computer

Science, 1998, 1447 : 611-616.

    [12] Ababneh J I, Bataineh M H. Linear phase FIR filter design using

particle swarm optimization and genetic algorithms [J]. Digital

Signal Processing, 2008, 18 (4): 657-668.

    [13] Mandal D, Bhattacharjee A K, Ghoshal S P. A novel particle swarm

optimization based optimal design of three-ring concentric circular

antenna array [C]//   IEEE International Conference on Advances

in Computing, Control, and Telecommunication Technologies.

Trivandrum, Kerala: IEEE, 2009: 385-389.

    [14] Ling S H, Iu H, Leung F H F, et al. Improved hybrid particle swarm

optimized wavelet neural network for modeling the development of

fluid dispensing for electronic packaging [J].   IEEE

Transactions on Industrial Electronics, 2008, 55 (9):

3447-3460.

    [15] Biswal B, Dash P K, Panigrahi B K. Power quality disturbance

classification using fuzzy C-means algorithm and adaptive particle

swarm optimization [J].   IEEE Transactions on Industrial

Electronics, 2009, 56 (1): 212-220.

    [16] Luitel B, Venayagamoorthy G K. Differential evolution particle

swarm optimization for digital filter design [C]//   IEEE

Congress on Evolutionary Computation (CEC 2008). Hong Kong, China:

IEEE, 2008: 3954-3961.

    [17] Herrmann O, Schussler W. Design of non-recursive digital

filters with linear phase [J].   Electronics Letters, 1970,

     6 (1): 329-330.

    [18] Sarangi A, Mahapatra R K, Panigrahi S K. DEPSO and

PSO-QI in digital filter design [J]. Expert Systems with

Applications, 2011, 38 (9): 10966-10973.

    [19] Mandal D, Ghoshal S P, Bhattacharjee A K. Application of evolutionary

optimization techniques for finding the optimal set of concentric

circular antenna array [J].   Expert Systems with Applications ,

2010, 38 (4): 2942-2950.

    [20] Mandal D, Ghoshal S P, Bhattacharjee A K. Radiation pattern optimization

for concentric circular antenna array with central element feeding

using craziness based particle swarm optimization [J].

International Journal of RF and Microwave Computer-Aided

Engineering, 2010, 20 (5): 577-586.