Abstract
Three Multi-Objective Differential Evolutions (MODEs) that differ in their selection schemes are applied to a real-world application, i.e., the multi-objective optimum design of the balanced Surface Acoustic Wave (SAW) filter used in cellular phones. In order to verify the optimality of the Pareto-optimal solutions obtained by the best MODE, those solutions are also compared with the solutions obtained by the weighted sum method. Besides, from the Principal Component Analysis (PCA) of the Pareto-optimal solutions, an obvious relationship between the objective function space and the design parameter space is disclosed.
Keywords
- Surface Acoustic Wave
- Trial Vector
- Objective Function Space
- Design Parameter Space
- Electric Output Signal
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Tagawa, K., Sasaki, Y., Nakamura, H. (2010). Optimum Design of Balanced SAW Filters Using Multi-Objective Differential Evolution. In: Deb, K., et al. Simulated Evolution and Learning. SEAL 2010. Lecture Notes in Computer Science, vol 6457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17298-4_50
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DOI: https://doi.org/10.1007/978-3-642-17298-4_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17297-7
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