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) plots, such as switching voltages or state resistances, we take into account the whole I-V curve measured in each RS cycle. This means going from a one-dimensional data set to a two-dimensional data set, in which every point of each I-V curve measured is included in the variability calculation. We introduce a new coefficient (named two-dimensional variability coefficient, 2DVC) that reveals additional variability information to which traditional one-dimensional analytical methods (such as the coefficient of variation) are blind. This novel approach provides a holistic variability metric for a better understanding of the functioning of resistive switching memories.
Keywords: functional data analysis; holistic methodology; resistive memories; variability; variability coefficient.