Method and system for multiple dataset gaussian process modeling
US8825456B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 15, 2010 |
| Grant date | Sep 2, 2014 |
| Priority date | — |
| Expiry date | Mar 10, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/10028
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of computerized data analysis and synthesis is described. First and second datasets of a quantity of interest are stored. A Gaussian process model is generated using the first and second datasets to compute optimized kernel and noise hyperparameters. The Gaussian process model is applied using the stored first and second datasets and hyperparameters to perform Gaussian process regression to compute estimates of unknown values of the quantity of interest. The resulting computed estimates of the quantity of interest result from a non-parametric Gaussian process fusion of the first and second measurement datasets. The first and second datasets may be derived from the same or different measurement sensors. Different sensors may have different noise and/or other characteristics.
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