Yield Estimation of a Memristive Sensor Array

Conference Paper (2020)
Author(s)

V Gupta (University of Rome Tor Vergata)

Saurabh Khandelwal (Oxford Brookes University)

Giulio Panunzi (University of Rome Tor Vergata)

E Martinelli (University of Rome Tor Vergata)

S Hamdioui (TU Delft - Quantum & Computer Engineering)

Abusaleh Jabir (Oxford Brookes University)

Marco Ottavi (University of Rome Tor Vergata)

Department
Quantum & Computer Engineering
DOI related publication
https://doi.org/10.1109/IOLTS50870.2020.9159727
More Info
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Publication Year
2020
Language
English
Department
Quantum & Computer Engineering
Pages (from-to)
1-2
ISBN (print)
978-1-7281-8188-2
ISBN (electronic)
978-1-7281-8187-5

Abstract

This paper proposes a method to calculate the yield of a memristor based sensor array considered as the probability that the chip provides acceptable sensing results when the array is affected by manufacturing defects. The modeling is based on a Markov Chain approach, in which each state represents an operating chip configuration and the state transitions take into account manufacturing defects. The proposed method is applicable to evaluate the yield with different fault models to achieve the comparative yield obtained by several redundancy allocations.

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