A Memristive Switching Uncertainty Model

In this paper, we endeavor to evaluate and model switching noise in resistive random access memory (RRAM) devices. Although noise is always present in physical systems, the sources of which can be attributed to many different effects, in this paper, 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 data set below and above the switching threshold and construct what we define as increment plots , $\Delta {R}$ versus ${R}$ . Then, through a detailed statistical analysis, we quantify the localized uncertainty among consecutive points using a sliding window of up to ${N}$ points accounting for any statistical artifacts that arise. By separating the data accumulated from programming and read-out and analyzing 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 behavior of uncertainty of the device during programming. This modeled surface can be used as an approximation of the noise behavior of the device or it can be readily incorporated as an additional component to existing switching models.