This paper presents an alternative approach for the
design of linear phase digital low pass FIR filter using Particle
Swarm Optimization with Constriction Factor and Inertia
Weight Approach (PSO-CFIWA). FIR filter design is a multimodal
optimization problem. The conventional gradient based
optimization techniques are not efficient for digital filter
design. Given the filter specification to be realized, PSO
algorithm generates a set of filter coefficients and tries to
meet the ideal frequency characteristic. In this paper, for the
given problem, the realization of the FIR filters of different
order has been performed. The simulation results have been
compared with the well accepted evolutionary algorithm such
as genetic algorithm (GA). The results justify that the proposed
filter design approach using PSO-CFIWA outperforms to that
of GA, not only in the accuracy of the designed filter but also
in the convergence speed and solution quality
%0 Journal Article
%1 rajibkardurbadalmandal2011filter
%A Rajib Kar, Durbadal Mandal, Dibbendu Roy
%A Ghoshal, Sakti Prasad
%D 2011
%E Das, Dr Vinu V
%J International Journal on Electrical and Power Engineering
%K Convergence FIR_Filter GA Optimization PSO
%N 2
%P 5
%T FIR Filter Design using Particle Swarm Optimization
with Constriction Factor and Inertia Weight Approach
%U http://doi.searchdl.org/01.IJEPE.2.2.162
%V 2
%X This paper presents an alternative approach for the
design of linear phase digital low pass FIR filter using Particle
Swarm Optimization with Constriction Factor and Inertia
Weight Approach (PSO-CFIWA). FIR filter design is a multimodal
optimization problem. The conventional gradient based
optimization techniques are not efficient for digital filter
design. Given the filter specification to be realized, PSO
algorithm generates a set of filter coefficients and tries to
meet the ideal frequency characteristic. In this paper, for the
given problem, the realization of the FIR filters of different
order has been performed. The simulation results have been
compared with the well accepted evolutionary algorithm such
as genetic algorithm (GA). The results justify that the proposed
filter design approach using PSO-CFIWA outperforms to that
of GA, not only in the accuracy of the designed filter but also
in the convergence speed and solution quality
@article{rajibkardurbadalmandal2011filter,
abstract = {This paper presents an alternative approach for the
design of linear phase digital low pass FIR filter using Particle
Swarm Optimization with Constriction Factor and Inertia
Weight Approach (PSO-CFIWA). FIR filter design is a multimodal
optimization problem. The conventional gradient based
optimization techniques are not efficient for digital filter
design. Given the filter specification to be realized, PSO
algorithm generates a set of filter coefficients and tries to
meet the ideal frequency characteristic. In this paper, for the
given problem, the realization of the FIR filters of different
order has been performed. The simulation results have been
compared with the well accepted evolutionary algorithm such
as genetic algorithm (GA). The results justify that the proposed
filter design approach using PSO-CFIWA outperforms to that
of GA, not only in the accuracy of the designed filter but also
in the convergence speed and solution quality},
added-at = {2012-09-22T08:09:21.000+0200},
author = {{Rajib Kar, Durbadal Mandal}, Dibbendu Roy and Ghoshal, Sakti Prasad},
biburl = {https://www.bibsonomy.org/bibtex/228a6be8ef1df45edf6077f2932a7ca05/ideseditor},
editor = {Das, Dr Vinu V},
interhash = {2330512712049753cdcdf3d08e769f69},
intrahash = {28a6be8ef1df45edf6077f2932a7ca05},
journal = {International Journal on Electrical and Power Engineering},
keywords = {Convergence FIR_Filter GA Optimization PSO},
month = {August},
number = 2,
pages = 5,
timestamp = {2012-09-22T08:09:21.000+0200},
title = {FIR Filter Design using Particle Swarm Optimization
with Constriction Factor and Inertia Weight Approach},
url = {http://doi.searchdl.org/01.IJEPE.2.2.162},
volume = 2,
year = 2011
}