• DocumentCode
    1257870
  • Title

    A Resist-Protection-Oxide Transistor With Adaptable Low-Frequency Noise for Stochastic Neuromorphic Computation in VLSI

  • Author

    Chiu, Tang-Jung ; King, Ya-Chin ; Gong, Jeng ; Tsai, Yi-Hung ; Chen, Hsin

  • Author_Institution
    Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
  • Volume
    32
  • Issue
    9
  • fYear
    2011
  • Firstpage
    1293
  • Lastpage
    1295
  • Abstract
    Noise is found to play a beneficial rather than harmful role for neural computation. For example, the sensory neurons exploit stochastic resonance to enhance their sensitivity. This finding has inspired several neuromorphic systems attempting to use noise for computation. Nevertheless, an adaptable noise source is essential for taking the most advantages of noise. This letter presents a resist-protection-oxide (RPO) transistor, which is a defect-rich transistor between the drain implant and the gate. The RPO defects enhance greatly the low-frequency noise of the transistor. The noise level is further adaptable over two decades by the drain voltage. Moreover, the transistor is fully compatible with the standard CMOS logic technology without requiring additional masks or process steps. All the features underpin the development of stochastic neuromorphic computation in integrated circuits.
  • Keywords
    field effect transistors; integrated circuit noise; resists; stochastic processes; CMOS logic technology; VLSI; adaptable low-frequency noise; adaptable noise source; defect-rich transistor; integrated circuit; neural computation; resist-protection-oxide field effect transistor; sensory neuron; stochastic neuromorphic computation; stochastic resonance; FETs; Implants; Logic gates; Low-frequency noise; Noise level; Defect screening; low-frequency noise; noise adaptability; resist protection oxide (RPO); stochastic computation;
  • fLanguage
    English
  • Journal_Title
    Electron Device Letters, IEEE
  • Publisher
    ieee
  • ISSN
    0741-3106
  • Type

    jour

  • DOI
    10.1109/LED.2011.2158384
  • Filename
    5930320