Random telegraph noise analysis to investigate the properties of active traps of HfO2-based RRAM in HRS

This paper presents statistical characterization of Random Telegraph Noise (RTN) in hafnium-oxide-based Resistive Random Access Memories (RRAMs) in High Resistive State (HRS). Complex RTN signals are analyzed exploiting a Factorial Hidden Markov Model (FHMM) approach, allowing to derive the statistical properties of traps responsible of the multi-level RTN measured in these devices. Noise characteristics in different reset conditions are explored to prove the existence of a direct relation between the reset voltage, the volume of the dielectric barrier created during the reset operation and the number of active traps contributing to the RTN.