An efficient and flexible window function for a memristor model and its analog circuit application

Abstract

The memristor is a novel nanostructured resistive tuning two-terminal electronic device that has been widely explored in the areas of neuromorphic computing systems, memory, digital circuits, analog circuits, and many more new applications. In this article, an efficient and flexible window function is presented for a linear drift memristor model. The proposed parametric cubic parabolic window function provides a unique feature (controllable window function discontinuity at the boundaries) to a linear drift memristor model by which the distorted pinched hysteresis loop problem is resolved and the number of programming resistance states of the memristor is improved. Five control parameters are introduced in the proposed window function in order to correct the existing problems (such as boundary effect, boundary lock and inflexibility) and are able to provide asymmetric nonlinearity at the boundaries of the device, making it feasible for tracking the resistive switching dynamic of a futuristic oxide-based memristive device with different inert electrodes. The proposed model is validated with a solution-processed ZnO-based fabricated memristive device. A programmable analog gain amplifier circuit is ultimately executed to simulate the utilization of the evolved memristor model, and the effect of memristance resolution is investigated.