An imanishian genetic algorithm for the optimum design of surface acoustic wave filter

Tagawa, Kiyoharu; Yamamoto, Takayuki; Igaki, Tsutomu; Seki, S.

doi:10.1109/cec.2003.1299436

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…Each IDT comprises some pairs of electrodes which are sometimes called fingers, while SMSA has numerous metal strips connected electrically in parallel. These components of the SAW filter are arranged bilateral symmetry on a piezoelectric substrate [8]. After this, we define the objective function of the optimization problem.…”

Section: Ga Used In Optimizationmentioning

confidence: 99%

“…We also applied a local search to the optimum design problem of a resonator type SAW filter [10], where we used the least equivalent circuit model of IDT. Unfortunately, we could rarely obtain a globally optimal or near-optimal structure of the SAW filter only by the local search, because the local optimization method doesn't have the ability to survey a vast region of the search space [8,9,11]. In gradient based methods typically used in optimization, the final result can depend strongly on the initial guess of the parameters.…”

Section: Introductionmentioning

confidence: 99%

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Frequency Response Optimization of Saw Filter using Canonical Genetic Algorithm

Chaudhary¹,

Priyanka²,

Duhan³

2011

IJCA

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An optimization program is employed to design the inter-digital transducer (IDT) structure of the surface acoustic wave (SAW) transducer to aim at improvement in the transducer characteristics and to improve the frequency response of SAW filter. In this paper, Genetic algorithm is used to optimize the response of a SAW filter. Then, the comparison of the response of SAW filter is done by using GA and without GA. The goal of optimization is to find best value for each variable in order to achieve minima or maxima of an objective function within the given constraints. In present study, three design variables of SAW filter i.e. number of finger pairs in input IDT (Np 1 ), number of finger pairs in `output IDT (Np 2 ), center to center distance between two electrodes in a finger pair (d), are optimized. After getting the optimized parameters of SAW filter, the frequency response of bandpass SAW filter is obtained, which is better as compared to the frequency response of SAW filter getting from other methods in terms of bandwidth and ripples amplitude.

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Section: Ga Used In Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Frequency Response Optimization of Saw Filter using Canonical Genetic Algorithm

Chaudhary¹,

Priyanka²,

Duhan³

2011

IJCA

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“…Therefore, according to the theory of the balanced network (Bockelman & Eisenstadt, 1995), we reorganize the entering signals a q (q=2, 3) and the leaving signals b p (p=2, 3) of the balanced port, or the pair of port-2 and port-3, respectively as shown in (6) From the definition shown in (6) and (7), the matrix S of conventional scattering parameters in (3) can be converted into the matrix S mix of mix-mode scattering parameters as follows. In order to evaluate the band-pass filter characteristics of the balanced SAW filter as well as the unbalanced one (Tagawa et al, 2003), we use the above mix-mode scattering parameters instead of conventional scattering parameters. Therefore, the standing wave ratios of the input-port E 3 and the output-port E 4 can be defined respectively in (9) and (10).…”

Section: Filter Characteristicsmentioning

confidence: 99%

Optimum Design of Balanced Surface Acoustic Wave Filters Using Evolutionary Computation

Tagawa¹

2009

Evolutionary Computation

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“…Therefore, in order to realize desirable frequency response characteristics of SAW filters, or their ideal functions, we need to decide their suitable structures. Because the structural design problem of SAW filters can't be solved with theory, optimum design techniques coupling iterative optimization methods with computer simulations are usually applied to the problem [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimum Design of DMS Filters Using Robust Engineering and Genetic Algorithm

Tagawa

Kojima

2006 IEEE International Conference on Evolutionary Computation

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A robust multi-objective optimization technique for the structural design of double mode surface acoustic wave (DMS) filters is proposed. The frequency response characteristics of DMS filters are governed primarily by their geometrical structures: the configurations of interdigital transducers (IDTs) and grating reflectors fabricated on piezoelectric substrates. For deciding suitable structures of DMS filters based on the computer simulation, the equivalent circuit models of IDT and grating reflector, which include several uncertain constant parameters, are usually used. In order to cope well with the designing imperfections caused by the inevitable dispersion of these constant parameters, the robust engineering, or the Taguchi method, is employed to evaluate the robustness of DMS filters. Then, because there is a trade-off relationship between the robustness of DMS filters and their ideal functions, the robust optimum design of DMS filters is formulated as a multiobjective optimization problem. Furthermore, an efficient multiobjective evolutionary algorithm, or revised NSGA-II, is used to obtain a set of Pareto-optimal solutions of the problem.

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An imanishian genetic algorithm for the optimum design of surface acoustic wave filter

Cited by 6 publications

References 13 publications

Frequency Response Optimization of Saw Filter using Canonical Genetic Algorithm

Frequency Response Optimization of Saw Filter using Canonical Genetic Algorithm

Optimum Design of Balanced Surface Acoustic Wave Filters Using Evolutionary Computation

Multi-Objective Optimum Design of DMS Filters Using Robust Engineering and Genetic Algorithm

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