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8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)

Research Article

Signal Amplification by Circular Single-Electron Oscillator Network with Stochastic Resonance

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BibTeX Plain Text
  • @INPROCEEDINGS{10.4108/icst.bict.2014.257850,
        author={Hiroyuki Otake and Kazuyoshi Ishimura and Tetsuya Asai and Takahide OYA},
        title={Signal Amplification by Circular Single-Electron Oscillator Network with Stochastic Resonance},
        proceedings={8th International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS)},
        publisher={ICST},
        proceedings_a={BICT},
        year={2015},
        month={2},
        keywords={neural network stochastic resonance single-electron circuit},
        doi={10.4108/icst.bict.2014.257850}
    }
    
  • Hiroyuki Otake
    Kazuyoshi Ishimura
    Tetsuya Asai
    Takahide OYA
    Year: 2015
    Signal Amplification by Circular Single-Electron Oscillator Network with Stochastic Resonance
    BICT
    ACM
    DOI: 10.4108/icst.bict.2014.257850
Hiroyuki Otake1,*, Kazuyoshi Ishimura2, Tetsuya Asai2, Takahide OYA1
  • 1: Yokohama National University
  • 2: Hokkaido University
*Contact email: otake-hiroyuki-zg@ynu.jp

Abstract

In this paper, a new type of a neuromorphic single-electron(SE) circuit is described and its operation is also evaluated by conducting Monte Carlo simulation. The circuit is expected as a new information-processing device. However, it is known that the circuit is very sensitive to noise and fluctuation, so that we have studied how to overcome such noise effect. Recently, unique technique that imitates stochastic resonance (SR) behavior in neural networks has been proposed to solve the problem of noise. We focus on internal noise for the SR system. To confirm the SR phenomenon caused by the internal noise, we change the circuit form to a circular structure. We can construct the circular neural network by using the SE circuit because the operation of them is similar to neurons. The proposed SE circuit network was able to show the SR phenomenon. Moreover, the circuit we found could amplify the output signal.

Keywords
neural network, stochastic resonance, single-electron circuit
Published
2015-02-02
Publisher
ICST
Appears in
ACM Digital Library
http://dx.doi.org/10.4108/icst.bict.2014.257850
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