Design of Optimal Digital IIR Filters by Using an Improved Immune Algorithm

Tsai, Jinn-Tsong; Chou, Jyh–Horng

doi:10.1109/tsp.2006.881248

Cited by 47 publications

(42 citation statements)

References 43 publications

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“…A co mmon way of realizing IIR filters is to cascade several first-order and second-order sections together [4][5] . Regardless of the filter type, the structure of cascading type digital IIR filter, is stated as [5] : [16,17] for magnitude is to be minimized. The magnitude response is specified at K equally spaced discrete frequency points in pass-band and stop-band.…”

Section: Iir Filter Design Problemmentioning

confidence: 99%

“…Genetic Algorith m (GA ) is not only capable of searching multid imensional and multimodal spaces but also optimizes co mplex and discontinuous functions that are hard to analyze mathematically. Therefore, researchers have developed design methods based on modern heuristics optimizat ion algorith ms such as genetic algorith ms [2][3][4][5][6][7][8][9][10] , particle swarm optimization [11] , seeker-optimizat ion-algorithm-based evolutionary method [12] , simulated annealing [13] , tabu search [14] , ant colony optimization [15] , hybrid taguchi genetic algorith m (HTGA) [16] ,immune algorith m (TIA) [17] and many more.…”

Section: Introductionmentioning

confidence: 99%

“…[5] , Tsai et al [16] and Tsai and Chou [17] for the LP, HP, BP, and BS filters. Finally, the conclusions and discussions are outlined in Section V.…”

Section: Introductionmentioning

confidence: 99%

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Digital IIR Filter Design using Real Coded Genetic Algorithm

Kaur¹,

Patterh²,

Dhillon³

2013

IJITCS

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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.

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Section: Iir Filter Design Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Digital IIR Filter Design using Real Coded Genetic Algorithm

Kaur¹,

Patterh²,

Dhillon³

2013

IJITCS

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“…The transfer function of IIR is represented by cascading first and second order sections to avoid the coefficient quantization problem which causes instability [4,8]. In cascade realization coefficient range is limited.…”

Section: Problem Statementmentioning

confidence: 99%

Optimal IIR Filter Design using Differential Evolution Algorithm

Goel¹,

Singh²

2014

IJCA

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Digital filter is mathematical algorithm that operates on discrete time signals. Different optimization algorithms can be utilized to determine the impulse response of coefficient of such a filter. Optimization problems for the design of digital filters are often complex, highly nonlinear, and multimodal in nature. The problems usually exhibit many local minima. Ideally, the optimization method should lead to the global optimum of the objective function with minimum amount of computation. Classical optimization methods are generally fast and efficient, and have been found to work reasonably well for the design of digital filters. These methods are very good in locating local minima. Therefore, they tend to locate minima in the locale of the initialization point. In recent years, a variety of algorithms have been proposed for global optimization including stochastic or heuristic algorithms; one such technique is Differential Evolution (DE). This paper presents an efficient DE based optimization technique for designing digital IIR filter by solving constrained multivariable optimization problem, to optimize the magnitude response of digital filters employing stability constraints using DE with opposition based strategy. KeywordsIIR Filter design, magnitude error (norm approximation error), Differential evolution Algorithm.

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“…Section III describes the basic harmony search algorithm and its modification. In Section IV, we apply the modified algorithm, along with the TIA approach [10] to the design of low-pass, high-pass, band pass and band stop filters. The results of the comparison are described in Section V, and are illustrated by convergence plots, frequency response plots, and pole-zero maps.…”

Section: Introductionmentioning

confidence: 99%