Intelligent autonomous feature extraction system using two hardware spiking neutral networks with spike timing dependent plasticity
US11157798B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 13, 2017 |
| Grant date | Oct 26, 2021 |
| Priority date | — |
| Expiry date | Nov 21, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the present invention provide an artificial neural network system for feature pattern extraction and output labeling. The system comprises a first spiking neural network and a second spiking neural network. The first spiking neural network is configured to autonomously learn complex, temporally overlapping features arising in an input pattern stream. Competitive learning is implemented as spike timing dependent plasticity with lateral inhibition in the first spiking neural network. The second spiking neural network is connected with the first spiking neural network through dynamic synapses, and is trained to interpret and label the output data of the first spiking neural network. Additionally, the labeled output of the second spiking neural network is transmitted to a computing device, such as a central processing unit for post processing.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.