Memristive Wilson–Cowan Neuron Models: Innovative Conceptual Framework and Programmable Analog and Digital Implementations

BARAN A. Y., Randrianantenaina J. L., Korkmaz N., KILIÇ R.

International Journal of Circuit Theory and Applications, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1002/cta.70219
  • Dergi Adı: International Journal of Circuit Theory and Applications
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, zbMATH
  • Anahtar Kelimeler: Field Programmable Analog Array (FPAA), Field Programmable Gate Array (FPGA), memristor, neuromorphic, Wilson–Cowan neuron model
  • Kayseri Üniversitesi Adresli: Evet

Özet

Since general purposes of memristors are not yet widely available as standard, off-the-shelf components, finding a reliable hardware equivalent is essential for accurately implementing a memristive neural system. With this motivation, we improve the piecewise-linear, piecewise quadratic, and cubic monotone-increasing functions-based memristive Wilson–Cowan (W-C) neuron models in this paper. After determining the control parameters of these three memristive W-C neuron models, we calculate their equilibrium points and Lyapunov exponents and then, we also illustrate the influence of the control parameters through bifurcation diagrams. Thus, the W-C neuron model is re-defined as including the essential characteristics of the memristors. Following the theoretical analysis of the memristive neuron models, we develop an alternative framework for spike-timing-dependent plasticity (STDP)-based network structures. Finally, the hardware confirmations of these models are built separately by using field programmable gate array (FPGA) and field programmable analog array (FPAA).