• DocumentCode
    2721892
  • Title

    Using fractal interpolation function encoded ultrasonic signals to train a neural network

  • Author

    Ali, Maaruf ; Meng, Xiaoping ; Clarkson, Trevor G. ; Taylor, John G.

  • Author_Institution
    Dept. of Electron. & Electr. Eng., King´´s Coll., London, UK
  • fYear
    1995
  • fDate
    34717
  • Firstpage
    42491
  • Lastpage
    42493
  • Abstract
    This abstract describes novel research in using fractally compressed ultrasonic transducer signals using Fractal Interpolation Function (FIF) codes to train probabilistic RAM neural (pRAM) networks in order to differentiate between flawed and unflawed concrete blocks. Two classes of ultrasonic spectrum are used, one for the flawed concrete block and the other for the unflawed concrete block. The spectrum thus obtained is fractally encoded using the one dimensional form of fractal compression known as fractal interpolation functions
  • Keywords
    concrete; fractals; interpolation; learning (artificial intelligence); neural nets; ultrasonic imaging; fractal compression; fractal interpolation function; neural network; probabilistic RAM; train; ultrasonic signals; ultrasonic transducer signals;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Fractals in Signal and Image Processing, IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19950020
  • Filename
    478248