An Evolutionary Approach to Automatic Generation of VHDL Code for Low-Power Digital Filters

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

@InProceedings{erba:2001:EuroGP,
  author =       "Massimiliano Erba and Roberto Rossi and 
                 Valentino Liberali and Andrea Tettamanzi",
  title =        "An Evolutionary Approach to Automatic Generation of
                 VHDL Code for Low-Power Digital Filters",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'2001",
  year =         "2001",
  editor =       "Julian F. Miller and Marco Tomassini and 
                 Pier Luca Lanzi and Conor Ryan and Andrea G. B. Tettamanzi and 
                 William B. Langdon",
  volume =       "2038",
  series =       "LNCS",
  pages =        "36--50",
  address =      "Lake Como, Italy",
  publisher_address = "Berlin",
  month =        "18-20 " # apr,
  organisation = "EvoNET",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, Evolvable
                 Hardware, Evolutionary Algorithms, Electronic Design,
                 Digital Filters, VHDL",
  ISBN =         "3-540-41899-7",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=2038&spage=36",
  DOI =          "doi:10.1007/3-540-45355-5_4",
  size =         "15 pages",
  abstract =     "An evolutionary algorithm is used to design a finite
                 impulse response digital filter with reduced power
                 consumption. The proposed design approach combines
                 genetic optimization and simulation methodology, to
                 evaluate a multi-objective fitness function which
                 includes both the suitability of the filter transfer
                 function and the transition activity of digital blocks.
                 The proper choice of fitness function and selection
                 criteria allows the genetic algorithm to perform a
                 better search within the design space, thus exploring
                 possible solutions which are not considered in the
                 conventional structured design methodology. Although
                 the evolutionary process is not guaranteed to generate
                 a filter fully compliant to specifications in every
                 run, experimental evidence shows that, when
                 specifications are met, evolved filters are much better
                 than classical designs both in terms of power
                 consumption and in terms of area, while maintaining the
                 same performance.",
  notes =        "EuroGP'2001, part of \cite{miller:2001:gp}",
}

Genetic Programming entries for Massimiliano Erba Roberto Rossi Valentino Liberali Andrea G B Tettamanzi

Citations