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A digital implementation of 2D Hindmarsh–Rose neuron

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Abstract

Different architectures and techniques have developed in the neuromorphic field to mimic and investigate the activity of biological neural networks. This paper presents a set of piece-wise linear approximations of a two-dimensional Hindmarsh–Rose neuron model for digital circuit implementation to achieve higher speeds and lower hardware costs in large-scale implementation of the biological neural networks. The performance of the model was evaluated with a time domain signal error. Synthesis and hardware implementation on a field-programmable gate array, as a proof of concept, indicates that the proposed model reproduces several neuronal behaviors similar to the original model with higher performance and considerably lower implementation costs.

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Authors and Affiliations

  1. Young Researchers and Elite Club, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

    Moslem Heidarpur

  2. University of Windsor, Windsor, Canada

    Arash Ahmadi

  3. Grand Valley State University, Grand Rapids, MI, USA

    Nabeeh Kandalaft

Authors
  1. Moslem Heidarpur
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  2. Arash Ahmadi
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  3. Nabeeh Kandalaft
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Correspondence to Arash Ahmadi.

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Heidarpur, M., Ahmadi, A. & Kandalaft, N. A digital implementation of 2D Hindmarsh–Rose neuron. Nonlinear Dyn 89, 2259–2272 (2017). https://doi.org/10.1007/s11071-017-3584-0

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