Memristor bridge-based artificial neuralweighting circuit

Hyongsuk Kim, Maheshwar Pd Sah, Changju Yang, Tamás Roska, Leon O. Chua

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A novel memristor bridge circuit which is able to perform zero, negative and positive synaptic weightings in neuron cells is proposed. It is composed of four memristors and three transistors for weighting operation and voltage-to-current conversion, respectively. It is compact as it can be fabricated in nano meter scale. It is power efficient since its operation is pulse-based. Its input terminals are utilized commonly for applying both weight programming and weight processing signals via time sharing. By programming on each memristor of the memristor bridge circuit, the signed weighting values can be set on the memristor bridge synapses. The features of proposed architecture are investigated via various simulations.

Original languageEnglish
Title of host publicationHandbook of Memristor Networks
PublisherSpringer International Publishing
Pages619-635
Number of pages17
ISBN (Electronic)9783319763750
ISBN (Print)9783319763743
DOIs
Publication statusPublished - Jan 1 2019

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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  • Cite this

    Kim, H., Sah, M. P., Yang, C., Roska, T., & Chua, L. O. (2019). Memristor bridge-based artificial neuralweighting circuit. In Handbook of Memristor Networks (pp. 619-635). Springer International Publishing. https://doi.org/10.1007/978-3-319-76375-0_22