Design of Optimal Linear Phase FIR High Pass Filter
using Improved Particle Swarm Optimization
D. Das (Eds.) ACEEE International Journal on Signal & Image Processing, 3 (1):
5(January 2012)
Abstract
This paper presents a novel approach for designing
a linear phase digital high pass FIR filter using Improved
Particle Swarm Optimization (IPSO) algorithm. Design of
FIR filter is a multi-modal optimization problem. The
conservative gradient based optimization techniques are not
efficient for digital filter design. Given the specifications for
the filters to be realized, IPSO algorithm generates a set of
optimal filter coefficients and tries to meet the ideal frequency
response characteristics. This paper presents the realization
of the optimal FIR high pass filter of filter order 20 as per
given problem statements. The simulation results have been
compared to those obtained from well accepted classical
algorithms like Park and McClellan algorithm (PM), and
evolutionary algorithms like genetic algorithm (GA) and
particle swarm optimization (PSO). The results rationalize
that the proposed optimal filter design approach using IPSO
outperforms PM, RGA, PSO in the accuracy of the designed
filter, as well as in the convergence speed and solution quality.
%0 Journal Article
%1 das2012design
%D 2012
%E Das, Dr Vinu V
%J ACEEE International Journal on Signal & Image Processing
%K Convergence IPSO PSO RGA
%N 1
%P 5
%T Design of Optimal Linear Phase FIR High Pass Filter
using Improved Particle Swarm Optimization
%U http://doi.searchdl.org/01.IJSIP.3.1.54
%V 3
%X This paper presents a novel approach for designing
a linear phase digital high pass FIR filter using Improved
Particle Swarm Optimization (IPSO) algorithm. Design of
FIR filter is a multi-modal optimization problem. The
conservative gradient based optimization techniques are not
efficient for digital filter design. Given the specifications for
the filters to be realized, IPSO algorithm generates a set of
optimal filter coefficients and tries to meet the ideal frequency
response characteristics. This paper presents the realization
of the optimal FIR high pass filter of filter order 20 as per
given problem statements. The simulation results have been
compared to those obtained from well accepted classical
algorithms like Park and McClellan algorithm (PM), and
evolutionary algorithms like genetic algorithm (GA) and
particle swarm optimization (PSO). The results rationalize
that the proposed optimal filter design approach using IPSO
outperforms PM, RGA, PSO in the accuracy of the designed
filter, as well as in the convergence speed and solution quality.
@article{das2012design,
abstract = {This paper presents a novel approach for designing
a linear phase digital high pass FIR filter using Improved
Particle Swarm Optimization (IPSO) algorithm. Design of
FIR filter is a multi-modal optimization problem. The
conservative gradient based optimization techniques are not
efficient for digital filter design. Given the specifications for
the filters to be realized, IPSO algorithm generates a set of
optimal filter coefficients and tries to meet the ideal frequency
response characteristics. This paper presents the realization
of the optimal FIR high pass filter of filter order 20 as per
given problem statements. The simulation results have been
compared to those obtained from well accepted classical
algorithms like Park and McClellan algorithm (PM), and
evolutionary algorithms like genetic algorithm (GA) and
particle swarm optimization (PSO). The results rationalize
that the proposed optimal filter design approach using IPSO
outperforms PM, RGA, PSO in the accuracy of the designed
filter, as well as in the convergence speed and solution quality.},
added-at = {2012-09-18T08:04:32.000+0200},
biburl = {https://www.bibsonomy.org/bibtex/2f8cff812ba6ca40ce5f34de2064f03f5/ideseditor},
editor = {Das, Dr Vinu V},
interhash = {599bcf29c5ddbd2b165ddd8a38d5ab89},
intrahash = {f8cff812ba6ca40ce5f34de2064f03f5},
journal = {ACEEE International Journal on Signal & Image Processing},
keywords = {Convergence IPSO PSO RGA},
month = {January},
number = 1,
pages = 5,
timestamp = {2012-09-18T08:04:32.000+0200},
title = {Design of Optimal Linear Phase FIR High Pass Filter
using Improved Particle Swarm Optimization},
url = {http://doi.searchdl.org/01.IJSIP.3.1.54},
volume = 3,
year = 2012
}