%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 }