Electronically Tunable Memristor Emulator Implemented Using a Single Active Element and Its Application in Adaptive Learning

Abstract

In recent times, much-coveted memristor emulators have found their use in a variety of applications such as neuromorphic computing, analog computations, signal processing, etc. Thus, a 100 MHz flux-controlled memristor emulator is proposed in this research brief. The proposed memristor emulator is designed using a single differential voltage current conveyor (DVCC), three PMOS transistors, and one capacitor. Among three PMOS transistors, two transistors are used to implement an active resistor, and one transistor is used as the multiplier required for the necessary memristive behaviors. Through simple adjustment of the switch, the proposed emulator can be operated in incremental as well as decremental configurations. The simulations are performed using a 180 nm technology node to validate the proposed design and are experimentally verified using AD844AN and CD4007 ICs. The memristor states of the proposed emulator are perfectly retained even in the absence of external stimuli, thereby ascertaining the non-volatility behavior. The robustness of the design is further analyzed using the PVT and Monte Carlo simulations, which suggest that the circuit operation is not hindered by the mismatch and process variations. A simple neuromorphic adaptive learning circuit based on the proposed memristor is also designed as an application.In recent times, much-coveted memristor emulators have found their use in a variety of applications such as neuromorphic computing, analog computations, signal processing, etc. Thus, a 100 MHz flux-controlled memristor emulator is proposed in this research brief. The proposed memristor emulator is designed using a single differential voltage current conveyor (DVCC), three PMOS transistors, and one capacitor. Among three PMOS transistors, two transistors are used to implement an active resistor, and one transistor is used as the multiplier required for the necessary memristive behaviors. Through simple adjustment of the switch, the proposed emulator can be operated in incremental as well as decremental configurations. The simulations are performed using a 180 nm technology node to validate the proposed design and are experimentally verified using AD844AN and CD4007 ICs. The memristor states of the proposed emulator are perfectly retained even in the absence of external stimuli, thereby ascertaining the non-volatility behavior. The robustness of the design is further analyzed using the PVT and Monte Carlo simulations, which suggest that the circuit operation is not hindered by the mismatch and process variations. A simple neuromorphic adaptive learning circuit based on the proposed memristor is also designed as an application.