Analytic Modeling for RRAM Based on Multistage Homotopy Analysis Method

Abstract

Resistive random access memory device (RRAM) has been widely used in various novel circuit systems, such as memory, artificial intelligence, and neural networks, due to its unique memory characteristics. However, there are very few studies focusing on analytic modeling of RRAM. In this article, modeling for solving analytic approximate solution to the state variable of RRAM, based on the proposed Multistage Homotopy Analysis Method (MuHAM), is proposed. Different from traditional HAM, the time span under consideration is divided into many subintervals, then the convergence control parameter in each subinterval is optimized to achieve high approximation accuracy. By simulating and comparing the obtained analytic solutions with solutions solved by other traditional homotopy-based modeling methodologies and by numerical analyses, we verified that MuHAM has higher Quality Factor (introduced to evaluate the model accuracy and computational cost comprehensively), hence improving the simulation efficiency. Besides the classical Hewlett-Packard (HP) RRAM, some current RRAMs are also verified. MuHAM also has the advantages of enabling both qualitative and quantitative analyses, and immunity to convergence issues. It is particularly suitable for the analytic modeling of the other novel memory devices having strong nonlinearity.