Approximation of digital circuits using cartesian genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

  author =       "Kagana.Sarath Babu and N. Balaji",
  booktitle =    "2016 International Conference on Communication and
                 Electronics Systems (ICCES)",
  title =        "Approximation of digital circuits using cartesian
                 genetic programming",
  year =         "2016",
  abstract =     "Digital circuits can be approximated in which the
                 exact functionality can be relaxed. Approximate
                 circuits are constructed such that the logic given by
                 the user is not implemented completely and hence their
                 functionality can be traded for area, delay and power
                 consumption. An evolutionary approach like Cartesian
                 Genetic programming (CGP) is used in this paper to make
                 automatic design process of digital circuits. The
                 quality of approximate circuits can be improved along
                 with the reduction of evolution time by using a
                 heuristic population seeding method which is embedded
                 into CGP. In particular, digital circuits like full
                 adder, 2 bit multiplier and 2 bit adder are addressed
                 in this paper. Experimental results are given where
                 random seeding mechanism is compared with heuristic
                 seeding methods.",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  DOI =          "doi:10.1109/CESYS.2016.7889978",
  month =        oct,
  notes =        "Also known as \cite{7889978}",

Genetic Programming entries for KaganaSarath Babu N Balaji