Implementation and Comparison of Algorithms for the extraction of RTN Parameters

The study of noise generated internally by devices, such as the Random Telegraph Noise (RTN), provides important information about the physical and atomistic properties of micro and nanoelectronic devices, among which are Resistive Random Access Memory (ReRAM) and MOSFET. In this work, we developed...

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Bibliographic Details
Published in:	2021 35th Symposium on Microelectronics Technology and Devices (SBMicro) pp. 1 - 4
Main Authors:	da Silveira, Claudia Theis, Exenberger Becker, Thales, Bockmann Alves, Pedro Augusto, Inacio Wirth, Gilson
Format:	Conference Proceeding
Language:	English
Published:	IEEE 23-08-2021
Subjects:	Algorithm Data mining Hidden Markov Model Hidden Markov models MOSFET Parameter extraction Performance evaluation Random Telegraph Noise Time measurement White noise
Online Access:	Get full text
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Summary:	The study of noise generated internally by devices, such as the Random Telegraph Noise (RTN), provides important information about the physical and atomistic properties of micro and nanoelectronic devices, among which are Resistive Random Access Memory (ReRAM) and MOSFET. In this work, we developed two methods to extract the RTN signal parameters. The first method is an algorithm based on Hidden Markov Model (HMM), a tool widely used to analyze stochastic signals. The second method is an algorithm based on the discretization of measurements. These algorithms perform the extraction of RTN signal parameters from synthetic and experimental data measured in electronic devices, such as ReRAM and MOSFET. In addition, a comparison between the methods is carried out. Finally, by comparing the results extracted by each method, a performance analysis of both implemented algorithms, in the presence of Gaussian (white) noise is made.
DOI:	10.1109/SBMicro50945.2021.9585757