• DocumentCode
    1970530
  • Title

    An integrated neurocomputing architecture for side-scan sonar target detection

  • Author

    Dzwonczyk, Mark ; Busa, Mark ; Sims, J. Terry ; Daud, Taher

  • Author_Institution
    Charles Stark Draper Lab., Cambridge, MA, USA
  • fYear
    1991
  • fDate
    15-17 Aug 1991
  • Firstpage
    169
  • Lastpage
    176
  • Abstract
    An integrated neurocomputing architecture developed for deployable, real-time pattern recognition applications is described. This architecture, called INCA, consists of a fully parallel, analog electronic, feedforward neural network coupled with a conventional microprocessor system. The first generation system, INCA/1, is currently under construction and employs existing analog neural network building block chips, with an off-the-shelf single-board computer. The proof-of-concept application for INCA/1 is the automatic detection of targets in sidescan sonar images. Preliminary simulations of the network, which account for some of the characteristics of the physical electronics, have shown excellent performance on real data without preprocessing
  • Keywords
    acoustic signal processing; pattern recognition; real-time systems; sonar; INCA; analog electronic; analog neural network building block chips; feedforward neural network; integrated neurocomputing architecture; proof-of-concept application; real-time pattern recognition applications; side-scan sonar target detection; sidescan sonar images; single-board computer; Analog computers; Application software; Computer architecture; Computer networks; Feedforward neural networks; Microprocessors; Neural networks; Pattern recognition; Sonar applications; Sonar detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks for Ocean Engineering, 1991., IEEE Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-0205-2
  • Type

    conf

  • DOI
    10.1109/ICNN.1991.163347
  • Filename
    163347