A memristive switching uncertainty model

In this paper we endeavour to evaluate and model switching noise in resistive random access memory devices (RRAM). Although noise is always present in physical systems, the sources of which can be attributed to many different effects, in this study we are focusing our attention on a specific type -- switching noise. Using alternating pulse programming and read trains across different voltages we acquire a large dataset below and above the switching threshold and construct what we define as increment plots, ΔR vs. R. Then, through a detailed statistical analysis, we quantify the localised uncertainty among consecutive points using a sliding window of up to N points accounting for any statistical artefacts that arise. By separating the data accumulated from programming and read-out and analysing them individually we can subtract a baseline noise floor from the overall switching uncertainty. In this way we effectively decouple it from other noise sources that affect the device at rest. In the end an F(R,V) surface can be extracted that closely follows the behaviour of uncertainty of the device during programming. This modelled surface can be used as an approximation of the noise behaviour of the device or it can be readily incorporated as an additional component to existing switching models.