Quantitative Study on Response of Joglekar and Biolek Memristor Models to Input Signal Variations

Abstract

This study aims to analyze the response of the Joglekar and Biolek memristor models to variations in input signals using LTspice simulations. Memristors, as key components in non-volatile memory technology and neuromorphic computing, have a unique ability to store information through changes in resistance that depend on the history of the current flowing. Although various mathematical models have been developed to represent the behavior of memristors, this research focuses on two of the most widely used models: Joglekar and Biolek. These two models differ in their mathematical approaches, particularly in the use of window functions to regulate the memristor's response to input signal variations. Simulations were performed with three different types of input signals: sinusoidal, square, and triangular waves, to evaluate the memristor's response to variations in signal frequency and amplitude. The data from the simulations were analyzed quantitatively using descriptive statistics, including mean, standard deviation, variance, median, and range calculations. The results show that the Joglekar model exhibits larger fluctuations compared to the Biolek model across all waveforms, particularly for the square wave. On the other hand, the Biolek model shows a more stable and consistent response. This study provides deeper insights into the advantages and limitations of each model in practical applications, especially in the development of memristor-based memory and neuromorphic computing systems