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The Chua's circuit has been considered as a paradigm for the investigation of chaos, but it still presents many unexplored dynamics. Chaotic hysteresis is an effect observed when the hysteresis phenomenon and chaotic dynamics phenomenon act simultaneously. It is an interesting phenomenon since it is observed in a variety of disciplines, and it has been utilized in explaining the mechanism of bursting oscillations, rich dynamics in thermal convection, and economic financial crisis, to mention a few. In this paper, we report the experimental observation of chaotic hysteresis in a Chua's electronic circuit driven by both a dc and a slow triangular voltage source. One and two hysteresis loops were observed in single and double scroll chaotic regimes, respectively. We present variations of the attractor that are induced by voltage changes, as well as the dependence of the hysteresis effect on both the driving frequency and the distance from the threshold passing from single to double-scroll chaotic regimes. Our results help in expanding our knowledge on unexplored dynamics of Chua's circuit as well as contribute to chaos control theory with a potential for applications. • Experimental observation of chaotic hysteresis in a Chua's circuit • The circuit was driven by both a DC and a slow triangular voltage source. • One and two hysteresis loops are observed. • The variations of the dynamic attractor due to voltage changes are presented and characterized. [ABSTRACT FROM AUTHOR]

Random telegraph noise (RTN) owns its very name to its assumed stochastic nature. In this paper, we follow up previous works that questioned this stochastic nature, and we investigate this assumption using experimentally measured noise coming from properly biased Ni/HfO 2 unipolar Resistive RAM memristor nanodevices. We have used established, well–known tools from nonlinear theory to examine the current–noise temporal series. Evaluation results show that this series appears to exhibit not a stochastic, but a deterministic chaotic behavior, also demostrating interesting fractal characteristics in 2D and 3D phase space projections. The presented results clearly advocate for a strong component of complex (chaotic) fluctuation of deterministic origin, instead of a typical (fully stochastic) RTN. This result could pave the path for an enhanced understanding of the mechanisms behind RTN emergence, as well as improve its noise models. • We have analyzed experimental time series RTN from Ni/HfO 2 unipolar Resistive RAM memristor nanodevices. • Established nonlinear dynamics evaluation tools have been utilized in order to characterize • The recorded RTN has been proved to be deterministic chaotic, possessing a fractal structure. • The studied nanodevice dynamics can embedded in a 5-dimensional phase space. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the reset transition in bipolar TiN/Ti/HfO 2 (10 nm)/Al 2 O 3 (2 nm)/W ReRAM devices using a tool that allows studying the temporal behaviour of these devices. This tool, the Dynamic Route Map (DRM), provides information about the temporal evolution of the state variable that governs the behaviour of the device, thus allowing an increased insight into resistive switching processes. Here, we show that this DRM is a powerful tool, that may help explaining some non intuitive behaviours of memristors, like the difference in the reset voltage when the inputs are from different frequency or shape. Using this tool, this fact can be explained as a different trajectory on a unique surface defining the device. As a first step, we have used two different models, one based on a physical description, and another one based on the mathematical definition of memristor as a non linear relation between charge and flux. We check that similar DRM can be obtained from both models. Additionally, several series of set-reset transitions have been measured using voltage ramps of different slopes. From the measured transitions, the corresponding resistance has been extracted and, assuming conductive filaments (CF) as the switching mechanism, the corresponding CF radius has been calculated. Using these data, we show that explanations from the model are also supported when using experimental data, thus proving the validity of the approach. [ABSTRACT FROM AUTHOR]