• DocumentCode
    2708270
  • Title

    A pulse-density modulation circuit exhibiting noise shaping with single-electron neurons

  • Author

    Kikombo, Andrew Kilinga ; Asai, Tetsuya ; Oya, Takahide ; Schmid, Alexandre ; Leblebici, Yusuf ; Amemiya, Yoshihito

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
  • fYear
    2009
  • fDate
    14-19 June 2009
  • Firstpage
    1600
  • Lastpage
    1605
  • Abstract
    We propose a bio-inspired circuit performing pulse-density modulation with single-electron devices. The proposed circuit consists of three single-electron neuronal units, receiving the same input and are connected to a common output. The output is inhibitorily fedback to the three neuronal circuits through a capacitive coupling, tuned to obtain a winners-share-all network operation. The circuit performance was evaluated through Monte-Carlo based computer simulations. We demonstrated that the proposed circuit possesses noise-shaping characteristics, where signal and noises are separated into low and high frequency bands respectively. This significantly improved the signal-to-noise ratio (SNR) by 4.34 dB in the coupled network, as compared to the uncoupled one. The noise-shaping properties are as a result of i) the inhibitory feedback between the output and the neuronal circuits, and ii) static noises (originating from device fabrication mismatches) and dynamic noises (as a result of thermally induced random tunneling events) introduced into the network.
  • Keywords
    Monte Carlo methods; neural nets; single electron devices; Monte-Carlo based computer simulations; bio-inspired circuit; capacitive coupling; device fabrication; neuronal circuits; noise shaping; pulse-density modulation circuit; single-electron devices; single-electron neuronal units; single-electron neurons; Circuit noise; Circuit optimization; Coupling circuits; Neurons; Noise shaping; Pulse circuits; Pulse modulation; Pulse shaping methods; Single electron devices; Tuned circuits;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2009. IJCNN 2009. International Joint Conference on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-3548-7
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2009.5178715
  • Filename
    5178715