DELTRON : neuromorphic architectures for delay based learning
We present a neuromorphic spiking neural network, the DELTRON, that can remember and store patterns by changing the delays of every connection as opposed to modifying the weights. The advantage of this architecture over traditional weight based ones is simpler hardware implementation without multipl...
| Päätekijät: | , , , |
|---|---|
| Muut tekijät: | |
| Aineistotyyppi: | Conference Paper |
| Kieli: | English |
| Julkaistu: |
2013
|
| Aiheet: | |
| Linkit: | https://hdl.handle.net/10356/101646 http://hdl.handle.net/10220/16341 |