Current controlled neuro-fuzzy membership function generation

Anuar Dorzhigulov, Bhaskar Choubey, Alex James Pappachen

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


Neuro-fuzzy systems are encouraging new approaches to mimic human-like decision making in presence of the vagueness and imprecision in the input data. However, majority of current implementations of these systems are limited to small-scale software designs, ignoring the potential advantages of the analogue hardware. This paper presents a completely tunable membership function generator, which is a vital part of designing neuro-fuzzy systems. Designed using a 130nm CMOS process, this circuit provides the ability to modify the shape as well as the mid-point of a widely used bell-shaped membership function. The circuit uses 11 transistors and provides this control of the membership function with an area of 0.9 µm 2 and power consumption of 12 µW. More importantly, only three control voltages are used without the need of any external digital control. Extensive simulation results are presented to verify the circuit.

Original languageEnglish
Title of host publication2018 IEEE 61st International Midwest Symposium on Circuits and Systems, MWSCAS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781538673928
Publication statusPublished - Jan 22 2019
Event61st IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2018 - Windsor, Canada
Duration: Aug 5 2018Aug 8 2018

Publication series

NameMidwest Symposium on Circuits and Systems
ISSN (Print)1548-3746


Conference61st IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2018

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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