Name
Title | ||
|---|---|---|
In-Hardware Learning of Multilayer Spiking Neural Networks on a Neuromorphic Processor |
Abstract | ||
|---|---|---|
Although widely used in machine learning, backpropagation cannot directly be applied to SNN training and is not feasible on a neuromorphic processor that emulates biological neuron and synapses. This work presents a spike-based backpropagation algorithm with biological plausible local update rules and adapts it to fit the constraint in a neuromorphic hardware. The algorithm is implemented on Intel... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/DAC18074.2021.9586323 | 2021 58th ACM/IEEE Design Automation Conference (DAC) |
Keywords | DocType | ISSN |
Training,Neuromorphics,Supervised learning,Backpropagation algorithms,Nonhomogeneous media,Biology,Hardware | Conference | 0738-100X |
ISBN | Citations | PageRank |
978-1-6654-3274-0 | 2 | 0.37 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amar Shrestha | 1 | 16 | 4.06 |
| haowen fang | 2 | 21 | 4.59 |
| Daniel Patrick Rider | 3 | 2 | 0.37 |
| Zaidao Mei | 4 | 6 | 0.79 |
| Qinru Qiu | 5 | 1120 | 102.58 |