Swarm Intelligence based Optimal Linear Phase FIR High Pass Filter Design using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach
In this paper, an optimal design of linear phase digital
high pass finite impulse response (FIR) filter using Particle Swarm
Optimization with Constriction Factor and Inertia Weight Approach
(PSO-CFIWA) has been presented. In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. The conventional gradient based optimization
techniques are not efficient for digital filter design. Given the filter
specifications to be realized, the PSO-CFIWA algorithm generates a
set of optimal filter coefficients and tries to meet the ideal frequency
response characteristic. In this paper, for the given problem, the
designs of the optimal FIR high pass filters of different orders have
been performed. The simulation results have been compared to those
obtained by the well accepted algorithms such as Parks and
McClellan algorithm (PM), genetic algorithm (GA). The results
justify that the proposed optimal filter design approach using PSOCFIWA
outperforms PM and GA, not only in the accuracy of the
designed filter but also in the convergence speed and solution
quality.
[1] Litwin L. "FIR and IIR digital filters". IEEE Potentials. 0278-6648,
2000, 28-31.
[2] Parks T W, Burrus C S. "Digital Filter Design". Wiley, New York, 1987.
[3] Parks T W, McClellan J H. "Chebyshev approximation for non recursive
digital filters with linear phase". IEEE Trans. Circuits Theory, CT-19
(1972) 189-194.
[4] McClellan J H, Parks T W, Rabiner L R. "A computer program for
designing optimum FIR linear phase digital filters". IEEE Trans. Audio
Electro acoust., AU-21 (1973) 506-526.
[5] Rabiner L R. "Approximate design relationships for low-pass FIR digital
filters". IEEE Trans. Audio Electro acoust., AU-21 (1973) 456-460.
[6] Herrmann O, Schussler W. "Design of non-recursive digital filters with
linear phase". Electron. Lett., 6 (1970), 329-330.
[7] 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 (2003) 634-639.
[8] Chen S. "IIR Model Identification Using Batch-Recursive Adaptive
Simulated Annealing Algorithm". In Proceedings of 6th Annual Chinese
Automation and Computer Science Conference, 2000, pp.151-155.
[9] Luitel B, Venayagamoorthy G K. "Differential Evolution Particle Swarm
Optimization for Digital Filter Design". 2008 IEEE Congress on
Evolutionary Computation (CEC 2008), PP. 3954-3961, 2008.
[10] 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.
[11] Kennedy J, Eberhart R. "Particle Swarm Optimization". in Proc. IEEE
int. Conf. On Neural Network, 1995.
[12] Eberhart R, Shi Y. "Comparison between Genetic Algorithms and
Particle Swarm Optimization". Proc. 7th Ann. Conf. on Evolutionary
Computation, San Diego, 2000.
[13] Ling S H, Iu H H C, Leung F H F, and Chan K Y. "Improved hybrid
particle swarm optimized wavelet neural network for modeling the
development of fluid dispensing for electronic packaging". IEEE Trans.
Ind. Electron., vol. 55, no. 9, pp. 3447-3460, Sep. 2008.
[14] Biswal B, Dash P K, and Panigrahi B K. "Power quality disturbance
classification using fuzzy C-means algorithm and adaptive particle
swarm optimization,". IEEE Trans. Ind. Electron., vol. 56, no. 1, pp.
212-220, Jan. 2009.
[15] Mandal D, Ghoshal S P, and Bhattacharjee A K. "Radiation Pattern
Optimization for Concentric Circular Antenna Array With Central
Element Feeding Using Craziness Based Particle Swarm Optimization".
International Journal of RF and Microwave Computer-Aided
Engineering, 20(5): 577-586, John Wiley & Sons, Inc., Sept. 2010.
[16] Mandal D, Ghoshal S P, and Bhattacharjee A K. "Application of
Evolutionary Optimization Techniques for Finding the Optimal set of
Concentric Circular Antenna Array. Expert Systems with Applications,
(Elsevier), vol. 38, pp. 2942-2950, 2010.
[17] Mandal D, Ghoshal S P, and Bhattacharjee A K. "Comparative Optimal
Designs of Non-uniformly Excited Concentric Circular Antenna Array
Using Evolutionary Optimization Techniques". IEEE Second
International Conference on Emerging Trends in Engineering and
Technology, ICETET-09 (2009), 619-624.
[18] Sarangi A, Mahapatra R M, Panigrahi S P. "DEPSO and PSO-QI in
digital filter design". Expert Systems with Applications,. Volume 38,
Issue 9, September 2011, Pages 10966-10973.
[1] Litwin L. "FIR and IIR digital filters". IEEE Potentials. 0278-6648,
2000, 28-31.
[2] Parks T W, Burrus C S. "Digital Filter Design". Wiley, New York, 1987.
[3] Parks T W, McClellan J H. "Chebyshev approximation for non recursive
digital filters with linear phase". IEEE Trans. Circuits Theory, CT-19
(1972) 189-194.
[4] McClellan J H, Parks T W, Rabiner L R. "A computer program for
designing optimum FIR linear phase digital filters". IEEE Trans. Audio
Electro acoust., AU-21 (1973) 506-526.
[5] Rabiner L R. "Approximate design relationships for low-pass FIR digital
filters". IEEE Trans. Audio Electro acoust., AU-21 (1973) 456-460.
[6] Herrmann O, Schussler W. "Design of non-recursive digital filters with
linear phase". Electron. Lett., 6 (1970), 329-330.
[7] 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 (2003) 634-639.
[8] Chen S. "IIR Model Identification Using Batch-Recursive Adaptive
Simulated Annealing Algorithm". In Proceedings of 6th Annual Chinese
Automation and Computer Science Conference, 2000, pp.151-155.
[9] Luitel B, Venayagamoorthy G K. "Differential Evolution Particle Swarm
Optimization for Digital Filter Design". 2008 IEEE Congress on
Evolutionary Computation (CEC 2008), PP. 3954-3961, 2008.
[10] 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.
[11] Kennedy J, Eberhart R. "Particle Swarm Optimization". in Proc. IEEE
int. Conf. On Neural Network, 1995.
[12] Eberhart R, Shi Y. "Comparison between Genetic Algorithms and
Particle Swarm Optimization". Proc. 7th Ann. Conf. on Evolutionary
Computation, San Diego, 2000.
[13] Ling S H, Iu H H C, Leung F H F, and Chan K Y. "Improved hybrid
particle swarm optimized wavelet neural network for modeling the
development of fluid dispensing for electronic packaging". IEEE Trans.
Ind. Electron., vol. 55, no. 9, pp. 3447-3460, Sep. 2008.
[14] Biswal B, Dash P K, and Panigrahi B K. "Power quality disturbance
classification using fuzzy C-means algorithm and adaptive particle
swarm optimization,". IEEE Trans. Ind. Electron., vol. 56, no. 1, pp.
212-220, Jan. 2009.
[15] Mandal D, Ghoshal S P, and Bhattacharjee A K. "Radiation Pattern
Optimization for Concentric Circular Antenna Array With Central
Element Feeding Using Craziness Based Particle Swarm Optimization".
International Journal of RF and Microwave Computer-Aided
Engineering, 20(5): 577-586, John Wiley & Sons, Inc., Sept. 2010.
[16] Mandal D, Ghoshal S P, and Bhattacharjee A K. "Application of
Evolutionary Optimization Techniques for Finding the Optimal set of
Concentric Circular Antenna Array. Expert Systems with Applications,
(Elsevier), vol. 38, pp. 2942-2950, 2010.
[17] Mandal D, Ghoshal S P, and Bhattacharjee A K. "Comparative Optimal
Designs of Non-uniformly Excited Concentric Circular Antenna Array
Using Evolutionary Optimization Techniques". IEEE Second
International Conference on Emerging Trends in Engineering and
Technology, ICETET-09 (2009), 619-624.
[18] Sarangi A, Mahapatra R M, Panigrahi S P. "DEPSO and PSO-QI in
digital filter design". Expert Systems with Applications,. Volume 38,
Issue 9, September 2011, Pages 10966-10973.
@article{"International Journal of Electrical, Electronic and Communication Sciences:64279", author = "Sangeeta Mandal and Rajib Kar and Durbadal Mandal and Sakti Prasad Ghoshal", title = "Swarm Intelligence based Optimal Linear Phase FIR High Pass Filter Design using Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach", abstract = "In this paper, an optimal design of linear phase digital
high pass finite impulse response (FIR) filter using Particle Swarm
Optimization with Constriction Factor and Inertia Weight Approach
(PSO-CFIWA) has been presented. In the design process, the filter
length, pass band and stop band frequencies, feasible pass band and
stop band ripple sizes are specified. FIR filter design is a multi-modal
optimization problem. The conventional gradient based optimization
techniques are not efficient for digital filter design. Given the filter
specifications to be realized, the PSO-CFIWA algorithm generates a
set of optimal filter coefficients and tries to meet the ideal frequency
response characteristic. In this paper, for the given problem, the
designs of the optimal FIR high pass filters of different orders have
been performed. The simulation results have been compared to those
obtained by the well accepted algorithms such as Parks and
McClellan algorithm (PM), genetic algorithm (GA). The results
justify that the proposed optimal filter design approach using PSOCFIWA
outperforms PM and GA, not only in the accuracy of the
designed filter but also in the convergence speed and solution
quality.", keywords = "FIR Filter; PSO-CFIWA; PSO; Parks and McClellanAlgorithm, Evolutionary Optimization Technique; MagnitudeResponse; Convergence; High Pass Filter", volume = "5", number = "8", pages = "1159-6", }