Synthesis of low-sensitivity second-order digital filter using genetic programming with automatically defined functions

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

@InProceedings{Uesaka:2000:ISCAS,
  author =       "Kazuyoshi Uesaka and Masayuki Kawamata",
  title =        "Synthesis of low-sensitivity second-order digital
                 filter using genetic programming with automatically
                 defined functions",
  booktitle =    "Proceedings of the IEEE International Symposium on
                 Circuits and Systems, ISCAS 2000",
  year =         "2000",
  volume =       "1",
  pages =        "359--362",
  address =      "Geneva",
  month =        "28-31 " # may,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, IIR digital
                 filter structures, S-expressions, automatically defined
                 functions, fitness measure, genetic programming, global
                 optimisation technique, low coefficient sensitivity,
                 low-sensitivity digital filter design, magnitude
                 sensitivity, second-order digital filter, subroutines,
                 synthesis method, IIR filters, digital filters,
                 filtering theory, iterative methods, optimisation,
                 sensitivity",
  DOI =          "doi:10.1109/ISCAS.2000.857104",
  size =         "5 pages",
  abstract =     "This paper proposes a synthesis method for low
                 coefficient sensitivity second-order IIR digital filter
                 structures using Genetic Programming with Automatically
                 Defined Functions (GP-ADF). In this paper, digital
                 filter structures are represented as S-expressions with
                 subroutines. It is easy to generate syntactically valid
                 S-expressions and perform the genetic operations
                 because the representation is suitable for GP. In a
                 numerical example, we use the fitness measure including
                 the magnitude sensitivity, and demonstrate that the
                 proposed method can synthesize efficiently very low
                 coefficient sensitivity filter structures",
}

Genetic Programming entries for Kazuyoshi Uesaka Masayuki Kawamata

Citations