Resistive memories are outstanding electron devices that have displayed a large potential in
a plethora of applications such as nonvolatile data storage, neuromorphic computing …

A revision of the different numerical techniques employed to extract resistive switching (RS)
and modeling parameters is presented. The set and reset voltages, commonly used for …

In order to study the device-to-device and cycle-to-cycle variability of switching voltages in 4-
kbit RRAM arrays, an alternative statistical approach has been adopted by using …

We present a new methodology to quantify the variability of resistive switching memories.
Instead of statistically analyzing few data points extracted from current versus voltage (I–V) …

We have analyzed variability in resistive memories (Resistive Random Access Memories,
RRAMs) making use of advanced numerical techniques to process experimental …

Time series statistical analyses (TSSA) have been employed to evaluate the variability of
resistive switching memories and to model the set and reset voltages for modeling purposes …

A comprehensive analysis of two types of artificial neural networks (ANN) is performed to
assess the influence of quantization on the synaptic weights. Conventional multilayer …

Abstract A Markovian Arrival Process with Marked arrivals is used to model a discrete-time
complex warm standby multi-state system in a well-structured way. The online unit is subject …

Memristive devices have emerged as promising alternatives to traditional complementary
metal-oxide semiconductor (CMOS)-based circuits in the field of neuromorphic systems …

The homogeneity problem for testing if more than two different samples come from the same
population is considered for the case of functional data. The methodological results are …