Genetic programming and its applications to the synthesis of digital logic
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gp-bibliography.bib Revision:1.8010
- @InProceedings{Dill:1997:PACRIM,
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author = "Karen M. Dill and James H. Herzog and
Marek A. Perkowski",
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title = "Genetic programming and its applications to the
synthesis of digital logic",
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booktitle = "IEEE Pacific Rim Conference on Communications,
Computers and Signal Processing, PACRIM 1997",
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year = "1997",
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volume = "2",
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pages = "823--826",
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address = "Victoria, BC, Canada",
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month = "20-22 " # aug,
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note = "Networking the Pacific Rim, 10 Years PACRIM
1987-1997",
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keywords = "genetic algorithms, genetic programming, EHW, logic
circuits, logic CAD, digital logic synthesis, arbitrary
logic expressions, logic synthesis, problem
applicability, optimization criterion, logic gates,
population sizes, complete function coverage,
experimental test results, randomly designed functions,
input variables, logic equations, function coverage,
training set size, small training sets, function
recognition",
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ISBN = "0-7803-3905-3",
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DOI = "doi:10.1109/PACRIM.1997.620386",
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size = "4 pages",
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abstract = "Genetic programming is applied to the synthesis of
arbitrary logic expressions. As a new method of logic
synthesis, this technique is uniquely advantageous in
its flexibility for both problem applicability and
optimisation criterion. A number of experiments were
conducted exploring this method with different types of
logic gates and population sizes. While complete
function coverage is not guaranteed, the best
experimental test results over eight randomly designed
functions, of four to seven input variables, have
produced logic equations with a 98.4percent function
coverage. In addition, the relation between the
training set size for the genetic program and function
coverage was also empirically explored. These
experiments showed that only small training sets were
necessary for function recognition.",
- }
Genetic Programming entries for
Karen M Dill
James H Herzog
Marek A Perkowski
Citations