System and method for spontaneous machine learning and feature extraction
US11151441B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Feb 8, 2017 |
| Grant date | Oct 19, 2021 |
| Priority date | — |
| Expiry date | Sep 24, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the present invention provide an artificial neural network system for improved machine learning, 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 spontaneously 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 output of the second spiking neural network is transmitted to a computing device, such as a CPU for post processing.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.