Analog Circuit Design Automation Using Neural Network-Based Two-Level Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Wang:2006:MLC,
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author = "Feng Wang and Yuan-Xiang Li",
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title = "Analog Circuit Design Automation Using Neural
Network-Based Two-Level Genetic Programming",
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booktitle = "2006 International Conference on Machine Learning and
Cybernetics",
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year = "2006",
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pages = "2087--2092",
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address = "Dalian",
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month = aug,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-4244-0061-9",
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DOI = "doi:10.1109/ICMLC.2006.258348",
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abstract = "The design of analog circuits starts with a high-level
statement of the circuit's desired behaviour and
requires creating a circuit that satisfies the
specified design goals. The difficulty of the problem
of analog circuit design is well known, and there is no
previously known general automated technique to design
an analog circuit from a high-level statement of the
circuit's desired behaviour. This paper proposes a
two-layer evolutionary scheme based on Genetic
Programming (GP) and Neural Network (NN), which uses a
divide-and-conquer approach to design the analog
circuits. Corresponding to the NN-TLGP, a new
representation of circuit has been proposed here and it
is more helpful to generate expectant circuit graphs.
This algorithm can perform the circuits with dynamical
size, circuit topology, and component values. The
experimental results on the two design work show that
this algorithm is efficient.",
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notes = "Department of Computer Science, Wuhan University,
Wuhan, 430072, China; State Key Lab of Software
Engineering, Wuhan University, Wuhan, 430072, China.",
- }
Genetic Programming entries for
Feng Wang
Yuanxiang Li
Citations