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Statements

Subject Item
n2:RIV%2F00216305%3A26230%2F09%3APU82613%21RIV10-MSM-26230___
rdf:type
skos:Concept n22:Vysledek
dcterms: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.
dcterms:title
Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming
skos:prefLabel
Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming Gate-Level Optimization of Polymorphic Circuits Using Cartesian Genetic Programming
skos:notation
RIV/00216305:26230/09:PU82613!RIV10-MSM-26230___
n3:aktivita
n15:P n15:Z
n3:aktivity
P(GA102/06/0599), Z(MSM0021630528)
n3:dodaniDat
n6:2010
n3:domaciTvurceVysledku
n11:7173873 n11:2192225
n3:druhVysledku
n16:D
n3:duvernostUdaju
n7:S
n3:entitaPredkladatele
n9:predkladatel
n3:idSjednocenehoVysledku
315986
n3:idVysledku
RIV/00216305:26230/09:PU82613
n3:jazykVysledku
n18:eng
n3:klicovaSlova
polymorphic circuit, circuit synthesis, evolutionary design, cartesian genetic programming
n3:klicoveSlovo
n4:cartesian%20genetic%20programming n4:polymorphic%20circuit n4:circuit%20synthesis n4:evolutionary%20design
n3:kontrolniKodProRIV
[6A0FA74301AA]
n3:mistoKonaniAkce
Trondheim
n3:mistoVydani
NA
n3:nazevZdroje
Proc. of 2009 IEEE Congress on Evolutionary Computation
n3:obor
n14:JC
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n13:GA102%2F06%2F0599
n3:rokUplatneniVysledku
n6:2009
n3:tvurceVysledku
Sekanina, Lukáš Gajda, Zbyšek
n3:typAkce
n20:WRD
n3:zahajeniAkce
2009-05-18+02:00
n3:zamer
n21:MSM0021630528
s:numberOfPages
6
n10:hasPublisher
IEEE Computational Intelligence Society
n12:isbn
978-1-4244-2958-5
n19:organizacniJednotka
26230