• DocumentCode
    3291802
  • Title

    Neural network detection

  • Author

    Ulanova, E.A. ; Nesteruk, D.A.

  • Author_Institution
    Tomsk Polytech. Univ., Tomsk
  • fYear
    2008
  • fDate
    24-28 March 2008
  • Firstpage
    122
  • Lastpage
    125
  • Abstract
    As is well known, neural network (NN) architecture is inspected by biology and they offer interesting properties for thermographic analysis and other fields as well, since they are adaptive and robust. A neural network (NN) is a highly interconnected set of small processors, each of which has a small memorization capability they learned from information submitted to them in the first place. Generally, the network is divided into layers and the parallel nature of NNs make them well suited to work on multiparameter problems.
  • Keywords
    Hopfield neural nets; neural net architecture; Hopfield-Kohonen growing cell structure; memorization capability; neural network architecture; neural network detection; Aluminum; Character generation; Clouds; Corrosion; Nanoparticles; Neural networks; Neurons; Propulsion; Solids; Toxicology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modern Technique and Technologies, 2008. MTT 2008. International Conference
  • Conference_Location
    Tomsk
  • Print_ISBN
    978-1-4244-1609-7
  • Type

    conf

  • DOI
    10.1109/SPCMTT.2008.4897517
  • Filename
    4897517