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Y. R. Zhou and J. He, “A Runtime Analysis of Evolutionary Algorithms for Constrained Optimization Problems,” IEEE Transactions on Evolutionary Computation, Vol. 11, No. 5, 2007, pp. 608-620. doi:10.1109/TEVC.2006.888929

has been cited by the following article:

• TITLE: Genetic Algorithm for the Design of Optimal IIR Digital Filters

  AUTHORS: Ranjit Singh, Sandeep K. Arya

  KEYWORDS: Digital Filter; Infinite-Impulse Response (IIR); Genetic Algorithm (GA); Optimization

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.3 No.3, August 31, 2012

  ABSTRACT: This paper presents the design of Optimal Infinite-Impulse Response (IIR) digital filters using Genetic Algorithm (GA). IIR filter is essentially a digital filter with Recursive responses. Since the error surface of digital IIR filters is generally nonlinear and multimodal, global optimization techniques are required in order to avoid local minima. This paper presents heuristic way for the designing IIR filters. GA is a powerful global optimization algorithm introduced in combinatorial optimization problems. The paper finds the optimum Coefficients of IIR digital filter through GA. Design of Lowpass and High pass IIR digital filter is proposed to provide estimate of transition band. It is found that the calculated values are more optimal than fda tool available for the design of filter in MATLAB. The simulation result of the employed examples shows an improvement on transition band and mean-square-error (MSE). The position of pole-zero is also presented to describe stability and results are compared with Simulated Annealing (SA) method.