• DocumentCode
    3424029
  • Title

    Binomial logic: extending stochastic computing to high-bandwidth signals

  • Author

    Kuehnel, Richard

  • Author_Institution
    Yakima Training Center, Yakima Res. Station, WA, USA
  • Volume
    2
  • fYear
    2002
  • fDate
    3-6 Nov. 2002
  • Firstpage
    1089
  • Abstract
    Stochastic logic, also known as stochastic computing, provides very low computation hardware area, fault tolerance, and efficient hardware implementations for high clock rates. It has long been defined as the processing of signals encoded as Bernoulli random sequences. This assumed definition has created its most notable restriction: the requirement to sample much faster than the Nyquist rate, severely limiting the allowable signal bandwidth. We demonstrate that stochastic logic can be extended beyond Bernoulli sequences to include binomial (N, p) representations where N > 1. By expanding the definition of stochastic computing we create a new design methodology that enables the engineer to obtain greater signal bandwidth by increasing the circuit size.
  • Keywords
    fault tolerant computing; logic programming; random processes; sequences; signal representation; signal sampling; stochastic programming; Bernoulli random sequences; Nyquist rate; binomial logic; binomial representations; circuit size; design methodology; efficient hardware implementation; fault tolerance; high clock rates; high-bandwidth signals; low computation hardware area; signal bandwidth; signal processing; signal sampling; single-pole filter; stochastic computing; stochastic logic; Bandwidth; Clocks; Design methodology; Fault tolerance; Hardware; Limiting; Logic; Random sequences; Signal processing; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2002. Conference Record of the Thirty-Sixth Asilomar Conference on
  • Conference_Location
    Pacific Grove, CA, USA
  • ISSN
    1058-6393
  • Print_ISBN
    0-7803-7576-9
  • Type

    conf

  • DOI
    10.1109/ACSSC.2002.1196952
  • Filename
    1196952