Yet Another Effective Dendritic Neuron Model Based on the Activity of Excitation and Inhibition

DOI Web Site 1 Citations 45 References
  • Yifei Yang
    Faculty of Engineering, University of Toyama, Toyama 930-8555, Japan
  • Chaofeng Zhang
    Advanced Institute of Industrial Technology, Tokyo 140-0011, Japan
  • Xiaosi Li
    Department of Engineering, Wesoft Company Ltd., Kawasaki 210-0024, Japan
  • Haotian Li
    Faculty of Engineering, University of Toyama, Toyama 930-8555, Japan
  • Yuki Todo
    Faculty of Electrical and Computer Engineering, Kanazawa University, Kanazawa 920-1192, Japan
  • Haichuan Yang
    Faculty of Engineering, University of Toyama, Toyama 930-8555, Japan

Bibliographic Information

Published
2023-04-02
Resource Type
journal article
Rights Information
  • https://creativecommons.org/licenses/by/4.0/
DOI
  • 10.3390/math11071701
Publisher
MDPI AG

Description

<jats:p>Neuronal models have remained an important area of research in computer science. The dendritic neuron model (DNM) is a novel neuronal model in recent years. Previous studies have focused on training DNM using more appropriate algorithms. This paper proposes an improvement to DNM based on the activity of excitation and proposes three new models. Each of the three improved models are designed to mimic the excitation and inhibition activity of neurons. The improved model proposed in this paper is shown to be effective in the experimental part. All three models and original DNM have their own strengths, so it can be considered that the new model proposed in this paper well enriches the diversity of neuronal models and contributes to future research on networks models.</jats:p>

Journal

  • Mathematics

    Mathematics 11 (7), 1701-, 2023-04-02

    MDPI AG

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