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Description
  • Polymorphic digital circuits contain ordinary and polymorphic gates. In the past, Cartesian Genetic Programming (CGP) has been applied to synthesize polymorphic circuits at the gate level. However, this approach is not scalable. Experimental results presented in this paper indicate that larger and more efficient polymorphic circuits can be designed by a combination of conventional design methods and evolutionary optimization (conducted by CGP). Proposed methods are evaluated on two benchmark circuits of variable input size.
  • Polymorphic digital circuits contain ordinary and polymorphic gates. In the past, Cartesian Genetic Programming (CGP) has been applied to synthesize polymorphic circuits at the gate level. However, this approach is not scalable. Experimental results presented in this paper indicate that larger and more efficient polymorphic circuits can be designed by a combination of conventional design methods and evolutionary optimization (conducted by CGP). Proposed methods are evaluated on two benchmark circuits of variable input size. (en)
Title
  • Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming
  • Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming (en)
skos:prefLabel
  • Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming
  • Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming (en)
skos:notation
  • RIV/00216305:26230/09:PU82613!RIV10-MSM-26230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/06/0599), Z(MSM0021630528)
http://linked.open...vai/riv/dodaniDat
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  • 315986
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/09:PU82613
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  • polymorphic circuit, circuit synthesis, evolutionary design, cartesian genetic programming (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6A0FA74301AA]
http://linked.open...v/mistoKonaniAkce
  • Trondheim
http://linked.open...i/riv/mistoVydani
  • NA
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  • Proc. of 2009 IEEE Congress on Evolutionary Computation
http://linked.open...in/vavai/riv/obor
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http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Sekanina, Lukáš
  • Gajda, Zbyšek
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • IEEE Computational Intelligence Society
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  • 978-1-4244-2958-5
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  • 26230
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