Artificial visual-tactile perception array for enhanced memory and neuromorphic computations  

作　　者：Jiaqi He Ruilai Wei Shuaipeng Ge Wenqiang Wu Jianchao Guo Juan Tao Ru Wang Chunfeng Wang Caofeng Pan 

机构地区：[1]CAS Center for Excellence in Nanoscience,Beijing Key Laboratory of Micro-nano Energy and Sensor,Beijing Institute of Nanoenergy and Nanosystems,Chinese Academy of Sciences,Beijing,the People's Republic of China [2]School of Nanoscience and Engineering,University of Chinese Academy of Sciences,Beijing,the People's Republic of China [3]Guangdong Research Center for Interfacial Engineering of Functional Materials,College of Materials Science and Engineering,Shenzhen University,Shenzhen,the People's Republic of China

出　　处：《InfoMat》2024年第3期81-94,共14页信息材料（英文）

基　　金：National Natural Science Foundation of China,Grant/Award Numbers:52002246,52192614,U22A2077,U20A20166,52125205,52372154;Natural Science Foundation of Beijing Municipality,Grant/Award Numbers:2222088,Z180011;Shenzhen Fundamental Research Project,Grant/Award Number:JCYJ20190808170601664;Shenzhen Science and Technology Program,Grant/Award Number:KQTD20170810105439418;Science and Technology Innovation Project of Shenzhen Excellent Talents,Grant/Award Number:RCBS20200714114919006;National Key R&D Program of China,Grant/Award Numbers:2021YFB3200304,2021YFB3200302;Fundamental Research Funds for the Central Universities。

摘　　要：The emulation of human multisensory functions to construct artificial perception systems is an intriguing challenge for developing humanoid robotics and cross-modal human–machine interfaces.Inspired by human multisensory signal generation and neuroplasticity-based signal processing,here,an artificial perceptual neuro array with visual-tactile sensing,processing,learning,and memory is demonstrated.The neuromorphic bimodal perception array compactly combines an artificial photoelectric synapse network and an integrated mechanoluminescent layer,endowing individual and synergistic plastic modulation of optical and mechanical information,including short-term memory,long-term memory,paired pulse facilitation,and“learning-experience”behavior.Sequential or superimposed visual and tactile stimuli inputs can efficiently simulate the associative learning process of“Pavlov's dog”.The fusion of visual and tactile modulation enables enhanced memory of the stimulation image during the learning process.A machine-learning algorithm is coupled with an artificial neural network for pattern recognition,achieving a recognition accuracy of 70%for bimodal training,which is higher than that obtained by unimodal training.In addition,the artificial perceptual neuron has a low energy consumption of~20 pJ.With its mechanical compliance and simple architecture,the neuromorphic bimodal perception array has promising applications in largescale cross-modal interactions and high-throughput intelligent perceptions.

关 键 词：artificial intelligent systems MECHANOLUMINESCENCE neuromorphic computing optoelectronic synapse visual-tactile perception 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]