Training a Probabilistic Graphical Model with Resistive Switching Electronic Synapses.

IEEE Transactions on Electron Devices(2016)

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摘要
Current large-scale implementations of deep learning and data mining require thousands of processors, massive amounts of off-chip memory, and consume gigajoules of energy. New memory technologies, such as nanoscale two-terminal resistive switching memory devices, offer a compact, scalable, and low-power alternative that permits on-chip colocated processing and memory in fine-grain distributed para...
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关键词
Phase change memory,Neurons,Resistive RAM,Data models,Neuromorphic engineering,Hardware,Probabilistic logic
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