Evolutionary Robust Design of Analog Filters Using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InCollection{hu:2007:ECdue,
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author = "Jianjun Hu and Shaobo Li and Erik D. Goodman",
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title = "Evolutionary Robust Design of Analog Filters Using
Genetic Programming",
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booktitle = "Evolutionary Computation in Dynamic and Uncertain
Environments",
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publisher = "Springer",
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year = "2007",
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editor = "Shengxiang Yang and Yew-Soon Ong and Yaochu Jin",
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volume = "51",
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series = "Studies in Computational Intelligence",
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pages = "479--496",
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chapter = "21",
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email = "hujianju@gmail.com",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-540-49772-1",
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DOI = "doi:10.1007/978-3-540-49774-5_21",
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abstract = "This chapter proposes a robust design approach that
exploits the open ended topological synthesis
capability of genetic programming (GP) to evolve robust
low pass and high pass analog filters. Compared with a
traditional robust design approach based on genetic
algorithms (GAs), the open-ended topology search based
on genetic programming and bond graph modeling (GPBG)
is shown to be able to evolve more robust filters with
respect to parameter perturbations than what was
achieved through parameter tuning alone, for the test
problems.",
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notes = "http://www.cse.sc.edu/~jianjunh/",
- }
Genetic Programming entries for
Jianjun Hu
Shaobo Li
Erik Goodman
Citations