Optoelectronic resistive random access memory for neuromorphic vision sensors
Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges...
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| Published in: | Nature nanotechnology Vol. 14; no. 8; pp. 776 - 782 |
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| Main Authors: | , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
England
Nature Publishing Group
01.08.2019
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| Subjects: | |
| ISSN: | 1748-3387, 1748-3395, 1748-3395 |
| Online Access: | Get full text |
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| Abstract | Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things. |
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| AbstractList | Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things. Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things.Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However, the complex circuitry of artificial visual systems based on conventional image sensors, memory and processing units presents serious challenges in terms of device integration and power consumption. Here we show simple two-terminal optoelectronic resistive random access memory (ORRAM) synaptic devices for an efficient neuromorphic visual system that exhibit non-volatile optical resistive switching and light-tunable synaptic behaviours. The ORRAM arrays enable image sensing and memory functions as well as neuromorphic visual pre-processing with an improved processing efficiency and image recognition rate in the subsequent processing tasks. The proof-of-concept device provides the potential to simplify the circuitry of a neuromorphic visual system and contribute to the development of applications in edge computing and the internet of things. |
| Author | Kang, Jinfeng Chen, Jiewei Lin, Ziyuan Yu, Shimeng Wong, H-S Philip Wang, Jingli Zhou, Feichi Chai, Yang Choy, Tsz Hin Zhou, Zheng Zhang, Ning |
| Author_xml | – sequence: 1 givenname: Feichi surname: Zhou fullname: Zhou, Feichi organization: Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 2 givenname: Zheng surname: Zhou fullname: Zhou, Zheng organization: Institute of Microelectronics, Peking University, Beijing, China – sequence: 3 givenname: Jiewei surname: Chen fullname: Chen, Jiewei organization: Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 4 givenname: Tsz Hin surname: Choy fullname: Choy, Tsz Hin organization: Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 5 givenname: Jingli surname: Wang fullname: Wang, Jingli organization: Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 6 givenname: Ning orcidid: 0000-0002-0755-1708 surname: Zhang fullname: Zhang, Ning organization: Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 7 givenname: Ziyuan surname: Lin fullname: Lin, Ziyuan organization: Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China – sequence: 8 givenname: Shimeng surname: Yu fullname: Yu, Shimeng organization: School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA – sequence: 9 givenname: Jinfeng surname: Kang fullname: Kang, Jinfeng organization: Institute of Microelectronics, Peking University, Beijing, China – sequence: 10 givenname: H-S Philip surname: Wong fullname: Wong, H-S Philip organization: Department of Electrical Engineering, Stanford University, Stanford, CA, USA – sequence: 11 givenname: Yang orcidid: 0000-0002-8943-0861 surname: Chai fullname: Chai, Yang email: ychai@polyu.edu.hk organization: Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China. ychai@polyu.edu.hk |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31308498$$D View this record in MEDLINE/PubMed |
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| Snippet | Neuromorphic visual systems have considerable potential to emulate basic functions of the human visual system even beyond the visible light region. However,... |
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| SubjectTerms | Artificial Organs BASIC (programming language) Bionics - instrumentation Circuits Edge computing Equipment Design Flight simulation Humans Information processing Internet of Things Light Memory devices Object recognition Optoelectronic devices Power consumption Random access memory Sensors Vision, Ocular Visual system |
| Title | Optoelectronic resistive random access memory for neuromorphic vision sensors |
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