Systems and methods for training neural networks based on concurrent use of current and recorded data
US8489528B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 28, 2010 |
| Grant date | Jul 16, 2013 |
| Priority date | — |
| Expiry date | May 31, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Various embodiments of the invention are neural network adaptive control systems and methods configured to concurrently consider both recorded and current data, so that persistent excitation is not required. A neural network adaptive control system of the present invention can specifically select and record data that has as many linearly independent elements as the dimension of the basis of the uncertainty. Using this recorded data along with current data, the neural network adaptive control system can guarantee global exponential parameter convergence in adaptive parameter estimation problems. Other embodiments of the neural network adaptive control system are also disclosed.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.