Wang et al., 2024 - Google Patents
MorphBungee: A 65-nm 7.2-mm 2 27-μJ/image Digital Edge Neuromorphic Chip with On-Chip 802-frame/s Multi-Layer Spiking Neural Network LearningWang et al., 2024
View PDF- Document ID
- 2189194405866381551
- Author
- Wang T
- Tian M
- Wang H
- Zhong Z
- He J
- Tang F
- Zhou X
- Lin Y
- Yu S
- Liu L
- Shi C
- Publication year
- Publication venue
- IEEE Transactions on Biomedical Circuits and Systems
External Links
Snippet
This paper presents a digital edge neuromorphic spiking neural network (SNN) processor chip for a variety of edge intelligent cognitive applications. This processor allows high- speed, high-accuracy and fully on-chip spike-timing-based multi-layer SNN learning. It is …
- 238000012421 spiking 0 title abstract description 24
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- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
- G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
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- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
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- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06F15/78—Architectures of general purpose stored programme computers comprising a single central processing unit
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- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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- G—PHYSICS
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