Abstract
This paper presents a novel computer-aided design method of Surface Acoustic Wave (SAW) filters which are widely used in the modern RF circuits of mobile communication systems. The performance of a SAW filter is specified by a number of criteria. Besides, the performance is deteriorated due to the uncertainties of physical coefficients and design parameters. In the multi-noisy-objective optimization problem of the SAW filter, the worst-case performance of a solution is considered based on the upper bounds of respective noisy-objective functions predicted statistically by multiple sampling. For finding various solutions for the problem effectively, a new evolutionary algorithm is proposed with three sample saving techniques. Finally, the influence of noise on the SAW filter is discussed through analysis of the obtained solutions.
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Tagawa, K., Harada, S. (2015). Multi-Noisy-Hard-Objective Robust Design of Balanced Surface Acoustic Wave Filters Based on Prediction of Worst-Case Performance. In: Mora, A., Squillero, G. (eds) Applications of Evolutionary Computation. EvoApplications 2015. Lecture Notes in Computer Science(), vol 9028. Springer, Cham. https://doi.org/10.1007/978-3-319-16549-3_50
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DOI: https://doi.org/10.1007/978-3-319-16549-3_50
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