Autors: Kirilov, S. M., Tsenov, G. T., Mladenov, V. M.
Title: A Simplified Analog Neuron Model with Modified Memristor-based Positive Synaptic Weights
Keywords: memristor , neural networks , synaptic weights , modeling an

Abstract: In this paper an analog circuit model for modified artificial neuron with memristor-based synapses is proposed. In this implementation each synaptic weight is realized by only one metal-oxide memristor, and this providing a vastly reduced circuit complexity. The summing and scaling device operation implementation is based on op-amp and a memristor. The activation function is realized by a simple circuit with CMOS transistors. The operation of the proposed neuron is analyzed both analytically and in LTSPICE environment and the derived results are compared and verified. The presented memristor-based neuron is a step for design of more complex neural networks with memristors.



    IEEE International Scientific Conference on Computer Science (COMSCI), pp. 1-6, 2023, Bulgaria, IEEE, DOI 10.1109/COMSCI59259.2023.10315912

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus