Automated passive filter synthesis using a novel tree representation and genetic programming
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gp-bibliography.bib Revision:1.8098
- @Article{CHS06,
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title = "Automated passive filter synthesis using a novel tree
representation and genetic programming",
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author = "Shoou-Jinn Chang and Hao-Sheng Hou and Yan-Kuin Su",
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journal = "IEEE Transactions on Evolutionary Computation",
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volume = "10",
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number = "1",
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month = feb,
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year = "2006",
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pages = "93--100",
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keywords = "genetic algorithms, genetic programming, RLC circuits,
circuit optimisation, network topology, passive
filters, GP-evolved circuits, RLC circuit analysis,
automated passive filter synthesis, circuit topology,
tree representation, Circuit analysis, circuit
representation, passive filter synthesis",
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ISSN = "1089-778X",
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DOI = "doi:10.1109/TEVC.2005.861415",
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abstract = "This paper proposes a novel tree representation which
is suitable for the analysis of RLC (i.e., resistor,
inductor, and capacitor) circuits. Genetic programming
(GP) based on the tree representation is applied to
passive filter synthesis problems. The GP is optimised
and then incorporated into an algorithm which can
automatically find parsimonious solutions without
predetermining the number of the required circuit
components. The experimental results show the proposed
method is efficient in three aspects. First, the
GP-evolved circuits are more parsimonious than those
resulting from traditional design methods in many
cases. Second, the proposed method is faster than
previous work and can effectively generate parsimonious
filters of very high order where conventional methods
fail. Third, when the component values are restricted
to a set of preferred values, the GP method can
generate compliant solutions by means of novel circuit
topology.",
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notes = "INSPEC Accession Number:8753451
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan,
Taiwan",
- }
Genetic Programming entries for
Shoou-Jinn Chang
Hao-Sheng Hou
Yan-Kuin Su
Citations