DocumentCode
2129412
Title
Behavioural modelling of memristive devices targeted to sensor interfaces
Author
Olumodeji, Olufemi A. ; Gottardi, Massimo
Author_Institution
Integrated Radiat. & Image Sensors, Fondazione Bruno Kessler (FBK), Trento, Italy
fYear
2015
fDate
3-5 Feb. 2015
Firstpage
1
Lastpage
4
Abstract
This paper describes the modelling and application of memristive systems in sensing technology. The proposed architecture is the adoption of memristive devices in place of laser trimming calibration technique to customise a sensor interface. Memristors can also work in combination with analogue and digital electronics to build adaptive systems. Several approaches have been made to overcome some of the disadvantages of laser trimming calibration such as replacing the trimmable resistors with programmable resistor arrays. The ability of the memristor to hold several resistance states can be exploited in an instrumentation amplifier having the memristor as a programmable feedback instead of an array of programmable resistors. A compact behavioural model of the memristor has been developed for the modelling and the simulation of complex circuits for sensor calibration. The model approximates the measurements of the memristor carried out in our labs, and also to simulate memristive logic gates.
Keywords
calibration; feedback amplifiers; instrumentation amplifiers; logic gates; memristors; analogue electronics; behavioural modelling; complex circuits; digital electronics; instrumentation amplifier; laser trimming calibration; memristive devices; memristive logic gates; programmable feedback; programmable resistor arrays; sensing technology; sensor calibration; sensor interfaces; trimmable resistors; Adaptation models; Instruments; Integrated circuit modeling; Logic gates; Memristors; Solid modeling; Instrumentation amplifier; logic gates; memory; memristor modelling; organic memristor; sensor calibration; switched memristor;
fLanguage
English
Publisher
ieee
Conference_Titel
AISEM Annual Conference, 2015 XVIII
Conference_Location
Trento
Type
conf
DOI
10.1109/AISEM.2015.7066780
Filename
7066780
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