Journal ArticleDOI
Ar+ ions irradiation induced memristive behavior and neuromorphic computing in monolithic LiNbO3 thin films
Xinqiang Pan,Xinqiang Pan,Yao Shuai,Wu Chuangui,Lu Zhang,Hongliang Guo,Hong Cheng,Peng Yun,Qiao Shijun,Wenbo Luo,Tao Wang,Xiangyu Sun,Huizhong Zeng,Jianwei Zhang,Wanli Zhang,Xin Ou,Nan Du,Heidemarie Schmidt +17 more
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TLDR
In this paper, the analogue memristive and related synaptic behavior of memristors based on single crystalline LiNbO3 thin films have been studied, and it has been shown that the local doping method significantly influences the linear regression process.About:
This article is published in Applied Surface Science.The article was published on 2019-08-01. It has received 14 citations till now. The article focuses on the topics: Neuromorphic engineering.read more
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Magnetic Elements for Neuromorphic Computing.
Tomasz Blachowicz,Andrea Ehrmann +1 more
TL;DR: A review of diverse approaches to implement neuromorphic functionalities in novel hardware using magnetic elements, published during the last years underlines the possible applications of magnetic materials and nanostructures in neuromorphic systems.
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Applications of Ion Beam Irradiation in Multifunctional Oxide Thin Films: A Review
TL;DR: Multifunctional oxide thin films exhibit a broad palette of properties, such as ferroelectricity, piezoelectricity, dielectricities, superconductivity, and metal-insulator transition as mentioned in this paper.
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Global modulatory heterosynaptic mechanisms in bio-polymer electrolyte gated oxide neuron transistors
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Resistive Switching Effects of Crystal-Ion-Slicing Fabricated LiNbO3 Single Crystalline Thin Film on Flexible Polyimide Substrate
Shitian Huang,Wenbo Luo,Xinqiang Pan,Jinyan Zhao,Qiao Shijun,Yao Shuai,Kaisheng Zhang,Xiaoyuan Bai,Gang Niu,Wu Chuangui,Wanli Zhang +10 more
Journal ArticleDOI
Real-Time Identification of Oxygen Vacancy Centers in LiNbO3 and SrTiO3 during Irradiation with High Energy Particles
TL;DR: In this paper, the authors focus their attention on the generation of oxygen vacancies by irradiation with high energy particles, which constitutes an efficient and reliable strategy to introduce, monitor, and characterize oxygen vacancies.
References
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Deep learning
TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
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Deep Learning
TL;DR: Deep learning as mentioned in this paper is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts, and it is used in many applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.
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Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
Geoffrey E. Hinton,Li Deng,Dong Yu,George E. Dahl,Abdelrahman Mohamed,Navdeep Jaitly,Andrew W. Senior,Vincent Vanhoucke,Patrick Nguyen,Tara N. Sainath,Brian Kingsbury +10 more
TL;DR: This article provides an overview of progress and represents the shared views of four research groups that have had recent successes in using DNNs for acoustic modeling in speech recognition.
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Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges
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Nanoscale Memristor Device as Synapse in Neuromorphic Systems
TL;DR: A nanoscale silicon-based memristor device is experimentally demonstrated and it is shown that a hybrid system composed of complementary metal-oxide semiconductor neurons and Memristor synapses can support important synaptic functions such as spike timing dependent plasticity.