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Improved IIR-type fractional order digital integrators using cat swarm optimization
Author(s) -
Shibendu Mahata,
Suman Kumar Saha,
Rajib Kar,
Durbadal Mandal
Publication year - 2018
Publication title -
turkish journal of electrical engineering and computer sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 30
eISSN - 1303-6203
pISSN - 1300-0632
DOI - 10.3906/elk-1606-480
Subject(s) - particle swarm optimization , infinite impulse response , multi swarm optimization , metaheuristic , differential evolution , mathematical optimization , swarm behaviour , mathematics , algorithm , parametric statistics , integrator , computer science , digital filter , filter (signal processing) , statistics , computer network , bandwidth (computing) , computer vision
Design of wideband infinite impulse response (IIR) digital fractional order integrators (DFOIs) based on a bio-inspired metaheuristic optimization approach called the cat swarm optimization (CSO) algorithm is presented in this paper. To investigate the efficiency of the proposed approach, the CSO-based DFOIs are evaluated against those of the approximations designed using real-coded genetic algorithm (RGA), standard particle swarm optimization (PSO), and differential evolution (DE) by different magnitude and phase response error metrics. Simulation results reveal the better frequency response of the CSO-based DFOIs in comparison with the competing designs. Both parametric and nonparametric statistical hypothesis tests validate the performance consistency of CSO. Comparisons with the cited literature confirm the efficacy of the proposed models.

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