• DocumentCode
    1627899
  • Title

    Fast and compact controllers with digital neural networks

  • Author

    Lazzizzera, I. ; Tecchiolii, G. ; Lee, P. ; Zorat, A. ; Sartori, A.

  • Author_Institution
    Dipt. di Fisica, Trento Univ., Italy
  • Volume
    1
  • fYear
    1997
  • Firstpage
    226
  • Abstract
    This paper presents a hardware solution for the implementation of high-speed control systems based on a neural architecture that, by using a novel number representation, reduces significantly the silicon area required by the realization of the architecture as a digital chip. The neural architecture was originally implemented as the TOTEM neural chip. The new number representation is based on logarithms so that the costly multipliers of TOTEM can be replaced by smaller adders, at the cost of introducing on-chip converters and paying an accuracy penalty. The resulting architecture TOTEM++ is then presented. It is shown that the accuracy loss does not degrade the quality of the overall results when used in the context of neural network computation
  • Keywords
    VLSI; digital control; encoding; microcontrollers; neural net architecture; ANN; Si; TOTEM neural chip; accuracy penalty; digital neural networks; high-speed control systems; neural architecture; number representation; on-chip converters; silicon area; Adders; Computer architecture; Computer networks; Control systems; Costs; Degradation; Digital control; Neural network hardware; Neural networks; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference, 1997. IMTC/97. Proceedings. Sensing, Processing, Networking., IEEE
  • Conference_Location
    Ottawa, Ont.
  • ISSN
    1091-5281
  • Print_ISBN
    0-7803-3747-6
  • Type

    conf

  • DOI
    10.1109/IMTC.1997.603947
  • Filename
    603947