Evolution of Signal Processing Algorithms using Vector Based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  title =        "Evolution of Signal Processing Algorithms using Vector
                 Based Genetic Programming",
  author =       "K. L. Holladay and K. A. Robbins",
  booktitle =    "15th International Conference on Digital Signal
  year =         "2007",
  pages =        "503--506",
  month =        jul,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, signal
                 classification, FIFTH, vector based genetic programming
                 language, signal classification problem, signal
                 processing algorithm, symbol rate estimation",
  DOI =          "doi:10.1109/ICDSP.2007.4288629",
  size =         "4 pages",
  abstract =     "This paper demonstrates that FIFTH, a new vector-based
                 genetic programming (GP) language, can automatically
                 derive very effective signal processing algorithms
                 directly from signal data. Using symbol rate estimation
                 as an example, we compare the performance of a standard
                 algorithm against an evolved algorithm. The evolved
                 algorithm uses a novel approach in developing a symbol
                 transition feature vector and achieves an impressive
                 97.7% overall accuracy in the defined problem domain,
                 far exceeding the performance of the standard
                 algorithm. These results suggest that vector based GP
                 approaches could be useful in developing more
                 expressive features for a large class of signal
                 processing and classification problems.",
  notes =        "P1333

                 p506 GP human competitive against DPDT

                 Also known as \cite{4288629}",

Genetic Programming entries for Kenneth L Holladay Kay A Robbins