Skip-connected self-recurrent spiking neural networks with joint intrinsic parameter and synaptic weight training
As an important class of spiking neural networks (SNNs), recurrent spiking neural networks (RSNNs) possess great computational power and have been widely used for processing sequential data like audio and text. However, most RSNNs suffer from two problems. First, due to the lack of architectural gui...
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| Format: | Article |
| Language: | English |
| Published: |
MIT Press Journals
2021
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| Subjects: | |
| Online Access: | View Fulltext in Publisher |