
Biography
Carol de Benito (Senior Member, IEEE) received the M.S. degree in physics and the Ph.D. degree in electronic engineering from the Universitat de les Illes Balears (UIB), Palma, Spain, in 1991 and 2012, respectively.,She is currently an Associate Professor with the Electronic Technology Group, Industrial and Construction Engineering Department, UIB. Her research interests include device and circuit modeling low-temperature CMOS design and memristor device and memristive system modeling. She has published more than 25 journal and conference papers and she has participated in several national and international projects.Associate Professor
Associate Professor
Publications:
Memristive Model of a Sb2Se3 Solar Cell
Memristors, first theorized in 1971 and experimentally confirmed in 2009, have attracted substantial research interest due to their unique characteristics. They are particularly significant in applications like neuromorphic computing and memory storage. However, memristive behavior is not always an isolated phenomenon; it can also emerge as a parasitic effect in various electronic devices. Despite this,…
Quantitative Description of the Stochastic Resonance in Chua Circuit Using the DFT of Switch-Phase Difference Distribution
Stochastic resonance (SR) can be defined as a phenomenon where the response of dynamical nonlinear systems to a weak input signal may be augmented due to the existance of noise tuned to the optimal level. Among others, the SR effect is quantified using measures as the signal-to-noise ratio, the output autocorrelation function, the residence time…
A circuital model of Sb2Se3 solar cells as memdiode devices for neuromorphic applications
Memristors are one of the four fundamental electrical components, relating electrical quantities such as current, voltage, charge (integral of current), and flux (integral of voltage). First proposed in 1971 and experimentally demonstrated in 2009, memristors have garnered significant research interest due to their unique properties. Among their many applications, neuromorphic computing and memory storage stand…
A Visual Odometry Artificial Intelligence‐Based Method for Trajectory Learning and Tracking Applied to Mobile Robots
Autonomous systems have demonstrated high performance in several applications. One of the most important is localisation systems, which are necessary for the safe navigation of autonomous cars or mobile robots. However, despite significant advances in this field, there are still areas open for research and improvement. Two of the most important challenges include the precise…
Evaluation of X-Ray Irradiation Effects on Solid Polymer Electrolyte Memristor Devices
In this study, we present the impact of irradiation on the memristive properties of solid polymer electrolyte memristor devices with a Ti/PMA/PEO/PMA/(Ti or Au) structure. The devices were measured before irradiation and after 1 krad and 2 krad total doses. The effects of irradiation appear to be an improvement in both conductance and hysteresis after…
Modelling thermal crosstalk on temperature driven memristors
In this paper we present a model describing the memristive behavior of a dual filament bulb that includes the thermal coupling between the filaments. The model is implemented with Matlab. The model, that represents the physical mechanisms behind the memristive behavior of filaments and coupling effect, is compiled according to the theoretical framework notation.
Unconventional security for IoT: Hardware and software implementation of a digital chaotic encrypted communication scheme
The two main issues in the area of the Internet of Things are low-resource consumption and secure data transmission. Conjugating both is fairly hard on ensuring security, leading to great efforts in research. The standard cryptography methods currently proposed are based on simplifications of standard protocols, but are still demanding on resources. Chaotic encryption is…
and Rodrigo Picos3, 4 1Physics Department, Aristotle University of Thessaloniki, Greece 2Physics Department, International Hellenic Uni-versity, Greece 3University of Balearic …
The two main issues in the area of the Internet of Things are low resources consumption and secure data transmission.
A Behavioural Compact Model for Programmable Neuromorphic ReRAM
In this work, we present a compact memristor model for bipolar neuromorphic ReRAM devices. The proposed model focuses on a behavioural high level description of the device, and it reproduces some of the most important characteristics (i.e. conductance, energy dissipation), using the number of pulses as the input variable instead of any electrical. Its functionality…
Exploiting optical nonlinear temporal coupling for implementing physical unclonable functions
In this work, we study the possibility of utilizing an LED-LDR pair for generating a Physical Unclonable Function. Towards this, the nonlinear response between an optically cou-pled LED-LDR pair, as well as the dynamic behavior of the LDR, were considered. The resulting behavior was highly nonlinear and strongly dependent on the actual physical properties of…
Implementation of reservoir computers using simulated electrostatically linked systems
Reservoir computing has become a domain of in-tense research during the last decade. It has emerged as an al-ternative approach to Artificial Neural Networks, demonstrating specific advantages. In this work, we explore the possibility of physical systems to be acting as reservoir computers. Specifically, we have simulated the performance of a reservoir consisting of a…
Implementation of a physically unclonable function using leds and ldrs
This work introduces a novel Physically Unclonable Function (PUF) based on the characteristics of Light-Emitting Diodes (LEDs) and Light-Detecting Resistors (LDRs) as long as these are combined. Specifically, we profit from the variations in the optical output of an LED caused by process variations, as well as from the variations in LDRs. In this way,…
Implementation of the Hindmarsh–Rose model using stochastic computing
The Hindmarsh–Rose model is one of the most used models to reproduce spiking behaviour in biological neurons. However, since it is defined as a system of three coupled differential equations, its implementation can be burdensome and impractical for a large number of elements. In this paper, we present a successful implementation of this model within…
On the chaotic nature of random telegraph noise in unipolar RRAM memristor devices
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/HfO2 unipolar Resistive RAM memristor nanodevices. We have used established, well–known tools from nonlinear theory to…
Empirical Modelling of ReRAM Measured Characteristics Using Charge and Flux
In this work, an empirical model based on a pure relation between charge and flux (aka an ideal memristor) has been proposed to fit the experimental data for ReRAM devices in flux charge domain. The model is able to capture the behavior with a very good accuracy, including also the behavior of the memconductance.
