Factorial Hidden Markov Model analysis of Random Telegraph Noise in Resistive Random Access Memories

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Published: Jan 15, 2014
DOI: https://doi.org/10.37936/ecti-eec.2014121.170814
Keywords:
RTN Multi-level FHMM Trapping Noise

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Francesco Maria Puglisi
DIEF - Universit à di Modena e Reggio Emilia
Paolo Pavan
DIEF - Universit à di Modena e Reggio Emilia

Abstract


This paper presents a new technique to analyze the characteristics of multi-level random telegraph noise (RTN). RTN is defined as an abrupt switching of either the current or the voltage between discrete values as a result of trapping/de-trapping activity. RTN signal properties are deduced exploiting a factorial hidden Markov model (FHMM). The proposed method considers the measured multi-level RTN as a superposition of many two-levels RTNs, each represented by a Markov chain and associated to a single trap, and it is used to retrieve the statistical properties of each chain. These properties (i.e. dwell times and amplitude) are directly related to physical properties of each trap.


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How to Cite
Puglisi, F. M., & Pavan, P. (2014). Factorial Hidden Markov Model analysis of Random Telegraph Noise in Resistive Random Access Memories. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 12(1), 24–29. https://doi.org/10.37936/ecti-eec.2014121.170814
Issue
Vol. 12 No. 1 (2014): Special Session from EDSSC 2013
Section
Signal Processing

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