• DocumentCode
    2329096
  • Title

    Artificial neural networks, where do we go next?

  • Author

    Hammerstrom, Dan

  • Author_Institution
    Comput. Sci. & Eng., Oregon Health & Sci. Univ., Portland, OR, USA
  • Volume
    4
  • fYear
    2004
  • fDate
    25-29 July 2004
  • Firstpage
    2989
  • Abstract
    Summary form only given. The possibilities of going to the next level after neural networks by creating new intelligent complex systems are discussed in This work. To create such complex systems, there are a number of important problems that must be solved. The problems presented are as follows: (a) scaling; (b) the degree of biological accuracy; (c) how to do system integration; and (d) hardware acceleration. Some examples of research in each area were also given in This work.
  • Keywords
    large-scale systems; neural nets; artificial neural networks; biological accuracy degree; cognitive psychology; computational neuroscience; hardware acceleration; intelligent complex systems; system integration; Artificial neural networks; Biological system modeling; Capacitive sensors; Computational intelligence; Computer science; Emulation; Hardware; Intelligent systems; Neurons; Psychology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-8359-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.2004.1381142
  • Filename
    1381142