Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/855
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dc.contributor.authorMajhi, B-
dc.contributor.authorPanda, G-
dc.contributor.authorChoubey, A-
dc.date.accessioned2009-05-20T02:25:20Z-
dc.date.available2009-05-20T02:25:20Z-
dc.date.issued2008-
dc.identifier.citationIEEE Congress on Evolutionary Computation, CEC, June 1-6, Hongkong, 2008. (IEEE World Congress on Computational Intelligence).en
dc.identifier.urihttp://dx.doi.org/10.1109/CEC.2008.4630836-
dc.identifier.urihttp://hdl.handle.net/2080/855-
dc.description.abstractThis paper introduces the application of particle swarm optimization (PSO) technique to identify the parameters of pole-zero plants or infinite impulse response (IIR) systems. The PSO is one of the evolutionary computing tools that performs a structured randomized search of an unknown parameter space by manipulating a population of parameter estimates to converge to a suitable solution with low computational complexity. This paper applies this powerful PSO tool to identify the parameters of standard IIR systems and compares the results with those obtained using the genetic algorithm (GA). The comparative results reveal that the PSO shows faster convergence, involves low complexity, yields minimum MSE level and exhibits superior identification performance in comparison to its GA counterpart.en
dc.format.extent220165 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherIEEEen
dc.subjectIIR filtersen
dc.subjectcomputational complexityen
dc.subjectgenetic algorithmsen
dc.subjectmean square error methodsen
dc.subjectparameter estimationen
dc.subjectparticle swarm optimisationen
dc.subjectpoles and zerosen
dc.titleEfficient scheme of pole-zero system identification using Particle Swarm Optimization techniqueen
dc.typeArticleen
Appears in Collections:Conference Papers

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