Fuzzy based design of digital IIR filter using ETLBO

Authors : DAMANPREET SINGH, JASPREET SINGH DHILLON

Pages : 4042-4062

View : 8 | Download : 6

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :In this paper, a population-based robust enhanced teaching--learning-based optimization insert ignore into journalissuearticles values(ETLBO); algorithm with reduced computational effort and high consistency is applied to design stable digital infinite-impulse response insert ignore into journalissuearticles values(IIR); filters in a multiobjective framework. Furthermore, a decision-making methodology based on fuzzy set theory is applied to handle nonlinear and multimodal design problems of the IIR digital filter. The original teaching--learning-based optimization insert ignore into journalissuearticles values(TLBO); algorithm has been remodeled by merging the concepts of opposition-based learning and migration for the selection of good candidates and to maintain diversity, respectively. A multiobjective IIR digital filter design problem takes into consideration magnitude and phase response of the filter simultaneously, while satisfying stability constraints on the coefficients of the filter. The order of the filter is controlled by a control gene whose value is also along with filter coefficients, to obtain the optimum order of the designed IIR filter. Results illustrate that ETLBO is more capable and efficient in comparison to other optimization methods for the design of all types of filter, i.e. high-pass, low-pass, band-stop, and band-pass IIR digital filters.
Keywords : Digital infinite impulse response filters, teaching learning based optimization, magnitude response, phase response, filter order