Efficient Hardware Implementation of a Multi-Layer Gradient-Free Online-Trainable Spiking Neural Network on FPGA
This paper presents an efficient hardware implementation of the recently proposed Optimised Deep Event-driven Spiking Neural Network Architecture (ODESA). ODESA is the first network to have end-to-end multi-layer online local supervised training without using gradients and has the combined adaptatio...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10755039/ |
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