标题
Reliability of analog resistive switching memory for neuromorphic computing
作者
关键词
-
出版物
Applied Physics Reviews
Volume 7, Issue 1, Pages 011301
出版商
AIP Publishing
发表日期
2020-01-02
DOI
10.1063/1.5124915
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Memristive crossbar arrays for brain-inspired computing
- (2019) Qiangfei Xia et al. NATURE MATERIALS
- Performance Impacts of Analog ReRAM Non-ideality on Neuromorphic Computing
- (2019) Yu-Hsuan Lin et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Resistive RAM Endurance: Array-Level Characterization and Correction Techniques Targeting Deep Learning Applications
- (2019) Alessandro Grossi et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- A Physics-Based Compact Model for CBRAM Retention Behaviors Based on Atom Transport Dynamics and Percolation Theory
- (2019) Yudi Zhao et al. IEEE ELECTRON DEVICE LETTERS
- Study on High-Density Integration Resistive Random Access Memory Array From Multiphysics Perspective by Parallel Computing
- (2019) Guodong Zhu et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Learning the signatures of the human grasp using a scalable tactile glove
- (2019) Subramanian Sundaram et al. NATURE
- Improving linearity by introducing Al in HfO2 as memristor synapse device
- (2019) sridhar chandrasekaran et al. NANOTECHNOLOGY
- Quick-and-Dirty: An Architecture for High-Performance Temporary Short Writes in MLC PCM
- (2019) Mingzhe Zhang et al. IEEE TRANSACTIONS ON COMPUTERS
- A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers
- (2018) Thomas E. Potok et al. ACM Journal on Emerging Technologies in Computing Systems
- Training Fully Connected Networks with Resistive Memories: Impact of device failures
- (2018) Louis P. Romero et al. FARADAY DISCUSSIONS
- Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
- (2018) Tom Young et al. IEEE Computational Intelligence Magazine
- Insight Into the Mechanism of Tail Bits in Data Retention of Vacancy-Modulated Conductive Oxide RRAM
- (2018) Sang-Gyu Koh et al. IEEE ELECTRON DEVICE LETTERS
- Equivalent-accuracy accelerated neural-network training using analogue memory
- (2018) Stefano Ambrogio et al. NATURE
- SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations
- (2018) Shinhyun Choi et al. NATURE MATERIALS
- Neuro-Inspired Computing With Emerging Nonvolatile Memorys
- (2018) Shimeng Yu PROCEEDINGS OF THE IEEE
- Efficient and self-adaptive in-situ learning in multilayer memristor neural networks
- (2018) Can Li et al. Nature Communications
- A molecular neuromorphic network device consisting of single-walled carbon nanotubes complexed with polyoxometalate
- (2018) Hirofumi Tanaka et al. Nature Communications
- Training Fully Connected Networks with Resistive Memories: Impact of device failures
- (2018) Louis P. Romero et al. FARADAY DISCUSSIONS
- Weighted Synapses Without Carry Operations for RRAM-Based Neuromorphic Systems
- (2018) Yan Liao et al. Frontiers in Neuroscience
- Mitigating Asymmetric Nonlinear Weight Update Effects in Hardware Neural Network Based on Analog Resistive Synapse
- (2018) Chih-Cheng Chang et al. IEEE Journal on Emerging and Selected Topics in Circuits and Systems
- Stuck-at Fault Tolerance in RRAM Computing Systems
- (2018) Lixue Xia et al. IEEE Journal on Emerging and Selected Topics in Circuits and Systems
- Compensated Synaptic Device for Improved Recognition Accuracy of Neuromorphic System
- (2018) Chuljun Lee et al. IEEE Journal of the Electron Devices Society
- Bidirectional Non-Filamentary RRAM as an Analog Neuromorphic Synapse, Part I: Al/Mo/Pr0.7Ca0.3MnO3 Material Improvements and Device Measurements
- (2018) Kibong Moon et al. IEEE Journal of the Electron Devices Society
- Sign backpropagation: An on-chip learning algorithm for analog RRAM neuromorphic computing systems
- (2018) Qingtian Zhang et al. NEURAL NETWORKS
- Toward on-chip acceleration of the backpropagation algorithm using nonvolatile memory
- (2017) P. Narayanan et al. IBM JOURNAL OF RESEARCH AND DEVELOPMENT
- HfZrOx-Based Ferroelectric Synapse Device With 32 Levels of Conductance States for Neuromorphic Applications
- (2017) Seungyeol Oh et al. IEEE ELECTRON DEVICE LETTERS
- Improved Conductance Linearity and Conductance Ratio of 1T2R Synapse Device for Neuromorphic Systems
- (2017) Kibong Moon et al. IEEE ELECTRON DEVICE LETTERS
- Brain Intelligence: Go beyond Artificial Intelligence
- (2017) Huimin Lu et al. MOBILE NETWORKS & APPLICATIONS
- An approximate backpropagation learning rule for memristor based neural networks using synaptic plasticity
- (2017) D. Negrov et al. NEUROCOMPUTING
- Face classification using electronic synapses
- (2017) Peng Yao et al. Nature Communications
- High-Performance Mixed-Signal Neurocomputing With Nanoscale Floating-Gate Memory Cell Arrays
- (2017) Farnood Merrikh-Bayat et al. IEEE Transactions on Neural Networks and Learning Systems
- Nanoionics-Enabled Memristive Devices: Strategies and Materials for Neuromorphic Applications
- (2017) Zhiyong Wang et al. Advanced Electronic Materials
- Multibit memory operation of metal-oxide bi-layer memristors
- (2017) Spyros Stathopoulos et al. Scientific Reports
- Improved Synaptic Behavior Under Identical Pulses Using AlOx/HfO2Bilayer RRAM Array for Neuromorphic Systems
- (2016) Jiyong Woo et al. IEEE ELECTRON DEVICE LETTERS
- TiOx-Based RRAM Synapse With 64-Levels of Conductance and Symmetric Conductance Change by Adopting a Hybrid Pulse Scheme for Neuromorphic Computing
- (2016) Jaesung Park et al. IEEE ELECTRON DEVICE LETTERS
- A Phase Change Memory Cell With Metal Nitride Liner as a Resistance Stabilizer to Reduce Read Current Noise for MLC Optimization
- (2016) SangBum Kim et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- HfO2/Al2O3multilayer for RRAM arrays: a technique to improve tail-bit retention
- (2016) Xueyao Huang et al. NANOTECHNOLOGY
- 3D Ta/TaOx/TiO2/Ti synaptic array and linearity tuning of weight update for hardware neural network applications
- (2016) I-Ting Wang et al. NANOTECHNOLOGY
- Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing
- (2016) Zhongrui Wang et al. NATURE MATERIALS
- Multilevel-Cell Phase-Change Memory: A Viable Technology
- (2016) Aravinthan Athmanathan et al. IEEE Journal on Emerging and Selected Topics in Circuits and Systems
- Memristors for Energy-Efficient New Computing Paradigms
- (2016) Doo Seok Jeong et al. Advanced Electronic Materials
- A Novel Program-Verify Algorithm for Multi-Bit Operation in HfO2 RRAM
- (2015) F. M. Puglisi et al. IEEE ELECTRON DEVICE LETTERS
- Cell-to-Cell and Cycle-to-Cycle Retention Statistics in Phase-Change Memory Arrays
- (2015) Maurizio Rizzi et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Noise-Induced Resistance Broadening in Resistive Switching Memory—Part I: Intrinsic Cell Behavior
- (2015) Stefano Ambrogio et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element
- (2015) Geoffrey W. Burr et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Fully parallel write/read in resistive synaptic array for accelerating on-chip learning
- (2015) Ligang Gao et al. NANOTECHNOLOGY
- Training and operation of an integrated neuromorphic network based on metal-oxide memristors
- (2015) M. Prezioso et al. NATURE
- A new spin on magnetic memories
- (2015) Andrew D. Kent et al. Nature Nanotechnology
- Nanoscale cation motion in TaOx, HfOx and TiOx memristive systems
- (2015) Anja Wedig et al. Nature Nanotechnology
- Ultra-Low-Energy Three-Dimensional Oxide-Based Electronic Synapses for Implementation of Robust High-Accuracy Neuromorphic Computation Systems
- (2014) Bin Gao et al. ACS Nano
- Noise as a Resource for Computation and Learning in Networks of Spiking Neurons
- (2014) Wolfgang Maass PROCEEDINGS OF THE IEEE
- A million spiking-neuron integrated circuit with a scalable communication network and interface
- (2014) P. A. Merolla et al. SCIENCE
- Current Conduction Model for Oxide-Based Resistive Random Access Memory Verified by Low-Frequency Noise Analysis
- (2013) Z. Fang et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Pattern classification by memristive crossbar circuits using ex situ and in situ training
- (2013) Fabien Alibart et al. Nature Communications
- First-principles simulation of oxygen diffusion in HfOx: Role in the resistive switching mechanism
- (2012) S. Clima et al. APPLIED PHYSICS LETTERS
- High precision tuning of state for memristive devices by adaptable variation-tolerant algorithm
- (2012) Fabien Alibart et al. NANOTECHNOLOGY
- Memristive devices for computing
- (2012) J. Joshua Yang et al. Nature Nanotechnology
- A High-Yield $\hbox{HfO}_{x}$-Based Unipolar Resistive RAM Employing Ni Electrode Compatible With Si-Diode Selector for Crossbar Integration
- (2011) X. A. Tran et al. IEEE ELECTRON DEVICE LETTERS
- A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O5−x/TaO2−x bilayer structures
- (2011) Myoung-Jae Lee et al. NATURE MATERIALS
- Resistance-dependent amplitude of random telegraph-signal noise in resistive switching memories
- (2010) Daniele Ielmini et al. APPLIED PHYSICS LETTERS
- Nanoscale Memristor Device as Synapse in Neuromorphic Systems
- (2010) Sung Hyun Jo et al. NANO LETTERS
- Learning long-range vision for autonomous off-road driving
- (2009) Raia Hadsell et al. Journal of Field Robotics
- Relationship between resistive switching characteristics and band diagrams ofTi/Pr1−xCaxMnO3junctions
- (2009) S. Asanuma et al. PHYSICAL REVIEW B
- Modeling of Programming and Read Performance in Phase-Change Memories—Part II: Program Disturb and Mixed-Scaling Approach
- (2008) Ugo Russo et al. IEEE TRANSACTIONS ON ELECTRON DEVICES
- Phase change materials and their application to random access memory technology
- (2008) Simone Raoux et al. MICROELECTRONIC ENGINEERING
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