Digital IIR Filter Design using Real Coded Genetic Algorithm

Abstract

Abstract-The paper develops a technique for the robust and stable design of digital infinite impulse response (IIR) filters. As the error surface of IIR filters is generally mu lti-modal, g lobal optimization techniques are required to design efficient digital IIR filter in order to avoid local minima. In this paper a real-coded genetic algorithm (RCGA ) with arith meticaverage-bound-blend crossover and wavelet mutation is applied to design the digital IIR filter. A mu lticriterion optimization is emp loyed as the design criterion to obtain the optimal stable IIR filter that satisfies the different performance requirements like min imizing the L p -norm appro ximat ion error and min imizing the ripple magnitude. The proposed real-coded genetic algorithm is effect ively applied to solve the mult icriterion, mu ltiparameter optimization problems of lo w-pass, high-pass, band-pass, and band-stop digital filters design. The computational experiments show that the proposed method is superior or atleast comparable to other algorith ms and can be efficiently used for h igher order filter design.

Design of Higher Order Digital IIR Low Pass Filter Using Hybrid Differential Evolution

“…The results obtained from MS-7 strategy are better than the results given by Tang et al [8], Tsai et al [14], Kaur et al [22] and Singh et al [23] shown in Table IV. The coefficient of low pass digital IIR filter having order 21 designed with mutation strategy MS-7 are given in Table V.…”

“…In order to overcome this problem and to find the global minima, global optimization techniques like genetic algorithm (GA) [3], differential evolution (DE) [7], particle swarm optimization (PSO) [5] artificial bee colony (ABC), predator prey optimization (PPO) etc. have been used by the researchers [4,10,11,16,19,20,22,23] to design stable digital IIR filters. In this paper, a hybrid technique with differential evolution (DE) method as a global search technique and binary successive approximation (BSA) based evolutionary search method as a local search technique is proposed.…”

Optimal design of IIR filters based on least ℓp‐norm using a novel meta‐heuristic algorithm

“…These are orthogonal genetic algorithm, 12 hybrid Taguchi GA, 13 hybrid genetic algorithm, 14 and real coded genetic algorithm. 15 The particle swarm optimization (PSO) has been applied successfully to the IIR filter designs. Krusienski and Jenkins 16 introduced the application of PSO technique to IIR adaptive filter structures.…”

“…Another different works based on GA are reported in the literatures. These are orthogonal genetic algorithm, hybrid Taguchi GA, hybrid genetic algorithm, and real coded genetic algorithm . The particle swarm optimization (PSO) has been applied successfully to the IIR filter designs.…”

An Approach for obtaining Least Noisy Signal using Kaiser Window and Genetic Algorithm

“…Thus a set of filtered signals is obtained. In the next step the approach behind the most commonly used evolutionary search algorithm namely concept of Genetic Algorithm [19,20,21,22] is used to find out the optimum signal with lowest amount of noise by using the set of filtered signals as initial population. Considering initial population is the starting point of the Genetic Algorithm where the initial population comprises set of possible solutions to the specified problem.…”