• DocumentCode
    2260267
  • Title

    Study of Coherence Resonance in Carbon Nanotube Gas-Ionization Sensor System Using Leaky Integrate-and-Fire Model

  • Author

    Guohua, Hui ; Xiaoling, Wu ; Lili, Wu ; Min, Pan ; Yuquan, Chen ; Xiaobin, Zhang

  • Author_Institution
    Sch. of Basic Med. Sci., Nanjing Meidical Univ., Nanjing
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Dec. 2008
  • Firstpage
    504
  • Lastpage
    508
  • Abstract
    Coherence resonance in carbon nanotube gas-ionization sensor system was focused in this article. Firstly, experimental step was held: Gaussian white noise was added to the system. With the increase of noise intensity, electrical breakdown density became more and more intensive. The sensor system reached its electrical breakdown state at a lower interelectrode potential. Secondly, Based on the former study of coherence resonance in single leaky integrate-and-fire (LIF) neuron model, a nano-neuron array was proposed to give an explanation to the experimental results. Potential of each nano-neuron in the nano-neuron array varied according to noise intensity shift. With proper noise intensity, the amount of excitatory nano-neurons was enough to generate spike trains, which is the corresponding period of compact electrical breakdown.
  • Keywords
    Gaussian noise; carbon nanotubes; electric breakdown; gas sensors; ionisation; white noise; Gaussian white noise; carbon nanotube gas-ionization sensor system; coherence resonance; electrical breakdown; electrical breakdown density; interelectrode potential; leaky integrate-and-fire model; leaky integrate-and-fire neuron model; noise intensity; Biomedical engineering; Carbon nanotubes; Coherence; Electric breakdown; Electrodes; Mathematical model; Neurons; Sensor systems; Stochastic resonance; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3497-8
  • Type

    conf

  • DOI
    10.1109/IITA.2008.497
  • Filename
    4739624