Reconstruction of polynomial systems from noisy time-series measurements using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "Vinay Varadan and Henry Leung",
  title =        "Reconstruction of polynomial systems from noisy
                 time-series measurements using genetic programming",
  journal =      "IEEE Transactions on Industrial Electronics",
  year =         "2001",
  volume =       "48",
  number =       "4",
  pages =        "742--748",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming, noise,
                 polynomials, signal reconstruction, accurate parameter
                 estimate, addition, embedding dimension, functional
                 operators, improved least-squares method,
                 multiplication, noisy time-series measurements,
                 orthogonal Euclidean distance, polynomial systems
                 reconstruction, time delay, unknown polynomial
  ISSN =         "0278-0046",
  DOI =          "doi:10.1109/41.937405",
  size =         "7 pages",
  abstract =     "The problem of functional reconstruction of a
                 polynomial system from its noisy time-series
                 measurement is addressed in this paper. The
                 reconstruction requires the determination of the
                 embedding dimension and the unknown polynomial
                 structure. The authors propose the use of genetic
                 programming (GP) to find the exact functional form and
                 embedding dimension of an unknown polynomial system
                 from its time-series measurement. Using functional
                 operators of addition, multiplication and time delay,
                 they use GP to reconstruct the exact polynomial system
                 and its embedding dimension. The proposed GP approach
                 uses an improved least-squares (ILS) method to
                 determine the parameters of a polynomial system. The
                 ILS method is based on the orthogonal Euclidean
                 distance to obtain an accurate parameter estimate when
                 the series is corrupted by measurement noise.
                 Simulations show that the proposed ILS-GP method can
                 successfully reconstruct a polynomial system from its
                 noisy time-series measurements",
  notes =        "CODEN: ITIED6 INSPEC Accession Number:7007126",

Genetic Programming entries for Vinay Varadan Henry Leung