A new design method for adaptive IIR system identi?cation using hybrid CPSO and DE

dc.contributor.authorSeck Tuoh Mora, Juan Carlos
dc.date.accessioned2018-07-04T20:46:21Z
dc.date.available2018-07-04T20:46:21Z
dc.date.issued2017-02-01
dc.description.abstractAdaptive in?nite impulse response filters have received much attention due to its utilization in a wide range of real-world applications. The design of the IIR filters poses a typically nonlinear, non- differentiable and multimodal problem in the estimation of the coef?cient parameters. The aim of the current study is the application of a novel hybrid optimization technique based on the combination of cellular particle swarm optimization and differential evolution called CPSO?DE for the optimal parameter estimation of IIR filters. DE is used as the evolution rule of the cellular part in CPSO to improve the performance of the original CPSO. Benchmark IIR systems commonly used in the specialized literature have been selected for tuning the parameters and demonstrating the effectiveness of the CPSO-DE method.es
dc.identifier.urihttps://repository.uaeh.edu.mx/bitstream/123456789/18745
dc.language.isoenes
dc.titleA new design method for adaptive IIR system identi?cation using hybrid CPSO and DEes
dc.typeArticlees

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