Systems and methods for providing a neural network having an elementary network description for efficient implementation of event-triggered plasticity rules
US8719199B2 · kind B2 · utility
34Cited by
1References
24Claims
0Family size
Assignee
Inventors
Key dates
| Filing date | Sep 21, 2011 |
| Grant date | May 6, 2014 |
| Priority date | — |
| Expiry date | May 30, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A simple format is disclosed and referred to as Elementary Network Description (END). The format can fully describe a large-scale neuronal model and embodiments of software or hardware engines to simulate such a model efficiently. The architecture of such neuromorphic engines is optimal for high-performance parallel processing of spiking networks with spike-timing dependent plasticity. The software and hardware engines are optimized to take into account short-term and long-term synaptic plasticity in the form of LTD, LTP, and STDP.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.