Nano-Net. 4th International ICST Conference, Nano-Net 2009, Lucerne, Switzerland, October 18-20, 2009. Proceedings

Research Article

Pulse-Density Modulation with an Ensemble of Single-Electron Circuits Employing Neuronal Heterogeneity to Achieve High Temporal Resolution

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  • @INPROCEEDINGS{10.1007/978-3-642-04850-0_8,
        author={Andrew Kikombo and Tetsuya Asai and Yoshihito Amemiya},
        title={Pulse-Density Modulation with an Ensemble of Single-Electron Circuits Employing Neuronal Heterogeneity to Achieve High Temporal Resolution},
        proceedings={Nano-Net. 4th International ICST Conference, Nano-Net 2009, Lucerne, Switzerland, October 18-20, 2009. Proceedings},
        proceedings_a={NANO-NET},
        year={2012},
        month={5},
        keywords={neuromorphic LSIs neural networks single-electron circuits},
        doi={10.1007/978-3-642-04850-0_8}
    }
    
  • Andrew Kikombo
    Tetsuya Asai
    Yoshihito Amemiya
    Year: 2012
    Pulse-Density Modulation with an Ensemble of Single-Electron Circuits Employing Neuronal Heterogeneity to Achieve High Temporal Resolution
    NANO-NET
    Springer
    DOI: 10.1007/978-3-642-04850-0_8
Andrew Kikombo1,*, Tetsuya Asai1, Yoshihito Amemiya1
  • 1: Hokkaido University, IST-M252
*Contact email: kikombo@sapiens-ei.eng.hokudai.ac.jp

Abstract

We investigated the implications of static noises in a pulse-density modulator based on Vestibulo-ocular Reflex model. We constructed a simple neuromorphic circuit consisting of an ensemble of single-electron devices and confirmed that static noises (heterogeneity in circuit parameters) introduced into the network indeed played an important role in improving the fidelity with which neurons could encode signals whose input frequencies are higher than the intrinsic response frequencies of single neurons. Through Monte-Carlo based computer simulations, we demonstrated that the heterogeneous network could corectly encode signals with input frequencies as high as 1 GHz, twice the range for single (or a network of homogeneous) neurons.