Abstract
Integrated circuits are approaching biological complexity in device count. Biological systems are fault tolerant, adaptive, and trainable, and the possibility exists for similar characteristics in ICs. The authors report a limited-interconnect, highly layered synthetic neural network that implements these ideas. These networks are specifically designed to scale to tens of thousands of processing elements on current production size dies. A compact analog cell, a training algorithm, and a limited-interconnect architecture which has demonstrated neuromorphic behavior are described.
| Original language | English (US) |
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| Title of host publication | Proceedings of the Custom Integrated Circuits Conference |
| Editors | Anon |
| Publisher | Publ by IEEE |
| State | Published - May 1989 |
| Event | Proceedings of the IEEE 1989 Custom Integrated Circuits Conference - San Diego, CA, SA Duration: May 15 1989 → May 18 1989 |
Other
| Other | Proceedings of the IEEE 1989 Custom Integrated Circuits Conference |
|---|---|
| City | San Diego, CA, SA |
| Period | 5/15/89 → 5/18/89 |
ASJC Scopus subject areas
- Electrical and Electronic Engineering