Prof. Han Wang from the Department of Electrical and Electronic Engineering and his team collaborated with Prof. Mark Hersam at Northwestern University, Prof. Jing Guo at the University of Florida and Prof. Jiangbin Wu at the Institute of Semiconductors, Chinese Academy of Science on the research for the topic “A Van Der Waals Interfacial Junction Transistor for Reconfigurable Fuzzy Logic Hardware”. The research is recently published by Nature Electronics on October 15, 2024.
Abstract:
Edge devices face challenges when implementing deep neural networks due to constraints on their computational resources and power consumption. Fuzzy logic systems can potentially provide more efficient edge implementations due to their compactness and capacity to manage uncertain data. However, their hardware realization remains difficult, primarily because implementing reconfigurable membership function generators using conventional technologies requires high circuit complexity and power consumption. Here we report a multigate van der Waals interfacial junction transistor based on a molybdenum disulfide/graphene heterostructure that can generate tunable Gaussian-like and π-shaped membership functions. By integrating these generators with peripheral circuits, we create a reconfigurable fuzzy controller hardware capable of nonlinear system control. This fuzzy logic system can also be integrated with a few-layer convolution neural network to form a fuzzy neural network with enhanced performance in image segmentation.
Paper: A Van Der Waals Interfacial Junction Transistor for Reconfigurable Fuzzy Logic Hardware
Link: https://www.nature.com/articles/s41928-024-01256-3