An Electronic Synapse Device Based on Metal Oxide Resistive Switching Memory for Neuromorphic Computation
Top Cited Papers
- 9 June 2011
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Electron Devices
- Vol. 58 (8), 2729-2737
- https://doi.org/10.1109/ted.2011.2147791
Abstract
The multilevel capability of metal oxide resistive switching memory was explored for the potential use as a single-element electronic synapse device. TiN/HfOx/AlOx/ Pt resistive switching cells were fabricated. Multilevel resistance states were obtained by varying the programming voltage amplitudes during the pulse cycling. The cell conductance could be continuously increased or decreased from cycle to cycle, and about 105 endurance cycles were obtained. Nominal energy consumption per operation is in the subpicojoule range with a maximum measured value of 6 pJ. This low energy consumption is attractive for the large-scale hardware implementation of neuromorphic computing and brain simulation. The property of gradual resistance change by pulse amplitudes was exploited to demonstrate the spike-timing-dependent plasticity learning rule, suggesting that metal oxide memory can potentially be used as an electronic synapse device for the emerging neuromorphic computation system.Keywords
This publication has 33 references indexed in Scilit:
- $\hbox{Al}_{2}\hbox{O}_{3}$-Based RRAM Using Atomic Layer Deposition (ALD) With 1-$\mu\hbox{A}$ RESET CurrentIEEE Electron Device Letters, 2010
- An Organic Nanoparticle Transistor Behaving as a Biological Spiking SynapseAdvanced Functional Materials, 2010
- Spike timing dependent plasticity: a consequence of more fundamental learning rulesFrontiers in Computational Neuroscience, 2010
- An electrically modifiable synapse array of resistive switching memoryNanotechnology, 2009
- Electrical Manipulation of Nanofilaments in Transition-Metal Oxides for Resistance-Based MemoryNano Letters, 2009
- A hybrid nanomemristor/transistor logic circuit capable of self-programmingProceedings of the National Academy of Sciences of the United States of America, 2009
- Ti O 2 anatase nanolayer on TiN thin film exhibiting high-speed bipolar resistive switchingApplied Physics Letters, 2006
- A VLSI Array of Low-Power Spiking Neurons and Bistable Synapses With Spike-Timing Dependent PlasticityIEEE Transactions on Neural Networks, 2006
- An excellent weight-updating-linearity EEPROM synapse memory cell for self-learning Neuron-MOS neural networksIEEE Transactions on Electron Devices, 1995
- Neuromorphic electronic systemsProceedings of the IEEE, 1990