Data driven evaluation and rejection of trained Gaussian process-based wireless mean and standard deviation models
US9838847B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 2, 2015 |
| Grant date | Dec 5, 2017 |
| Priority date | — |
| Expiry date | Mar 25, 2036 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W4/023
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Disclosed are apparatus and methods for providing outputs; e.g., location estimates, based on trained Gaussian processes. A computing device can determine trained Gaussian processes related to wireless network signal strengths, where a particular trained Gaussian process is associated with one or more hyperparameters. The computing device can designate one or more hyperparameters. The computing device can determine a hyperparameter histogram for values of the designated hyperparameters of the trained Gaussian processes. The computing device can determine a candidate Gaussian process associated with one or more candidate hyperparameter value for the designated hyperparameters. The computing device can determine whether the candidate hyperparameter values are valid based on the hyperparameter histogram. The computing device can, after determining that the candidate hyperparameter values are valid, add the candidate Gaussian process to the trained Gaussian processes. The computing device can provide an estimated location output based on the trained Gaussian processes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.