An Online Unsupervised Structural Plasticity Algorithm for Spiking Neural Networks
In this paper, we propose a novel winner-take-all (WTA) architecture employing neurons with nonlinear dendrites and an online unsupervised structural plasticity rule for training it. Furthermore, to aid hardware implementations, our network employs only binary synapses. The proposed learning rule is...
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| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/80901 http://hdl.handle.net/10220/41059 |
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| Institution: | Nanyang Technological University |
| Language: | English |