This paper presents a new technique to analyze the characteristics of multi-level random telegraph noise (RTN) in HfOX RRAM. RTN is characterized by abrupt switching of either the current or the voltage between discrete values as a result of trapping/de-trapping activity while reading the RRAM cell. RTN statistical 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 RTN, 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
FHMM analysis for Multi-Defect Spectroscopy in HfOX RRAM / Puglisi, Francesco Maria; Pavan, Paolo. - (2013), pp. 47-48. (Intervento presentato al convegno Riunione Annuale GE 2013 tenutosi a Udine (Italy) nel 17-19 Giugno 2013).
FHMM analysis for Multi-Defect Spectroscopy in HfOX RRAM
PUGLISI, Francesco Maria;PAVAN, Paolo
2013
Abstract
This paper presents a new technique to analyze the characteristics of multi-level random telegraph noise (RTN) in HfOX RRAM. RTN is characterized by abrupt switching of either the current or the voltage between discrete values as a result of trapping/de-trapping activity while reading the RRAM cell. RTN statistical 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 RTN, 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 trapPubblicazioni consigliate
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