Memory association circuit based on memristor for neural networks

Memristors have been favored in artificial intelligence, neural networks, and chaotic circuits, especially in neural synapses because of their unique advantages such as resistance variability, nonvolatile nature, and nanometer size. Benefits such as integration scale and low power consumption contribute toward simulating the biological synaptic function. Compared with memory association circuits using traditional CMOS transistors, memristors will reduce the complexity of the circuit and the power consumption. Therefore, it is greatly promising to use memristors as synapses to construct neural networks to mimic human brain functions. This paper successfully establishes a recognition circuit based on memristors to recognize some characteristics (size, color, shape, and smooth) of fruits, which is a learning function. After a few seconds, the output signal voltage drops, and this is a forgetting function. Through the establishment of a recognition circuit, the neural network and human complex behavior were simulated. This work lays the foundation for further research of human neural networks.

Automated summary

This study successfully establishes a recognition circuit based on memristors to recognize characteristics of fruits, demonstrating learning and forgetting functions and simulating neural networks and complex human behaviors. The research lays the foundation for further exploration of human neural networks.