Systems and methods for converting discrete wavelets to tensor fields and using neural networks to process tensor fields
US10789331B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Aug 26, 2019 |
| Grant date | Sep 29, 2020 |
| Priority date | — |
| Expiry date | Aug 26, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems and methods for detecting and identifying anomalies within a discrete wavelet database. In one implementation, the system may include one or more memories storing instructions and one or more processors configured to execute the instructions. The instructions may include instructions to receive a new wavelet, convert the net transaction to a wavelet, convert the wavelet to a tensor using an exponential smoothing average, calculate a difference field between the tensor and a field having one or more previous transactions represented as tensors, perform a weighted summation of the difference field to produce a difference vector, apply one or more models to the difference vector to determine a likelihood of the new wavelet representing an anomaly, and add the new wavelet to the field when the likelihood is below a threshold.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.