Generalized bell-shaped membership function generation circuit for memristive neural networks

Anuar Dorzhigulov, Alex James

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A generalized bell-shaped function is an essential building block for a neuro-fuzzy systems and radial basis function neural networks. With the advent of edge computing, analog neuro-chips can potentially speed-up the near sensor computing. In this paper, we present a generalized bell function generator circuit for machine learning architectures. The circuit design of generalized bell-shaped function as the hybrid CMOS-Memristor that is compatible with typical memristive crossbar architecture is presented, where it uses three memristors to control the output current shape. Designed circuit occupies 10 µm2 and consumes less than 4.1 µW. The proposed circuit could be used as a standalone neuron for radial basis function neural network, as demonstrated in this work.

Original languageEnglish
Title of host publication2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728103976
DOIs
Publication statusPublished - Jan 1 2019
Event2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Sapporo, Japan
Duration: May 26 2019May 29 2019

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2019-May
ISSN (Print)0271-4310

Conference

Conference2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019
CountryJapan
CitySapporo
Period5/26/195/29/19

Fingerprint

Membership functions
Memristors
Neural networks
Networks (circuits)
Function generators
Fuzzy systems
Neurons
Learning systems
Sensors

Keywords

  • Fuzzy Circuits and Systems
  • Machine Learning
  • Memristor
  • Neuro-Fuzzy architectures
  • Radial basis function

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Dorzhigulov, A., & James, A. (2019). Generalized bell-shaped membership function generation circuit for memristive neural networks. In 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings [8702214] (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS.2019.8702214

Generalized bell-shaped membership function generation circuit for memristive neural networks. / Dorzhigulov, Anuar; James, Alex.

2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8702214 (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Dorzhigulov, A & James, A 2019, Generalized bell-shaped membership function generation circuit for memristive neural networks. in 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings., 8702214, Proceedings - IEEE International Symposium on Circuits and Systems, vol. 2019-May, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019, Sapporo, Japan, 5/26/19. https://doi.org/10.1109/ISCAS.2019.8702214
Dorzhigulov A, James A. Generalized bell-shaped membership function generation circuit for memristive neural networks. In 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8702214. (Proceedings - IEEE International Symposium on Circuits and Systems). https://doi.org/10.1109/ISCAS.2019.8702214
Dorzhigulov, Anuar ; James, Alex. / Generalized bell-shaped membership function generation circuit for memristive neural networks. 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (Proceedings - IEEE International Symposium on Circuits and Systems).
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