A Novel Evolutionary Algorithm for Designing Robust Analog Filters
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- @Article{li:2018:Algorithms,
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author = "Shaobo Li and Wang Zou and Jianjun Hu",
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title = "A Novel Evolutionary Algorithm for Designing Robust
Analog Filters",
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journal = "Algorithms",
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year = "2018",
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volume = "11",
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number = "3",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "1999-4893",
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URL = "https://www.mdpi.com/1999-4893/11/3/26",
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DOI = "doi:10.3390/a11030026",
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abstract = "Designing robust circuits that withstand environmental
perturbation and device degradation is critical for
many applications. Traditional robust circuit design is
mainly done by tuning parameters to improve system
robustness. However, the topological structure of a
system may set a limit on the robustness achievable
through parameter tuning. This paper proposes a new
evolutionary algorithm for robust design that exploits
the open-ended topological search capability of genetic
programming (GP) coupled with bond graph modelling. We
applied our GP-based robust design (GPRD) algorithm to
evolve robust lowpass and highpass analog filters.
Compared with a traditional robust design approach
based on a state-of-the-art real-parameter genetic
algorithm (GA), our GPRD algorithm with a fitness
criterion rewarding robustness, with respect to
parameter perturbations, can evolve more robust filters
than what was achieved through parameter tuning alone.
We also find that inappropriate GA tuning may mislead
the search process and that multiple-simulation and
perturbed fitness evaluation methods for evolving
robustness have complementary behaviours with no
absolute advantage of one over the other.",
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notes = "also known as \cite{a11030026}",
- }
Genetic Programming entries for
Shaobo Li
Wang Zou
Jianjun Hu
Citations