Neural network kernels for signal processing in lieu of digital signal processing in radio receivers
US11342946B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 22, 2021 |
| Grant date | May 24, 2022 |
| Priority date | — |
| Expiry date | Mar 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/047
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An artifact-suppressing neural network (NN) kernel comprising at least one neural network, implemented in replacement of a DSP, provides comparable or better performance under non-edge conditions, and superior performance under edge conditions, due to the ease of updating the NN kernel training without enlarging its computational footprint or latency to address a new edge condition. In embodiments, the NN kernel can be implemented in a field programmable gate array (FPGA) or application specific integrated circuit (ASIC), which can be configured as a direct DSP replacement. In various embodiments, the NN kernel training can be updated in near real time when a new edge condition is encountered in the field. The NN kernel can include DCC lower layers and dense upper layers. Initial NN kernel training can require fewer examples. Example embodiments include a noise suppression NN kernel and a modem NN kernel.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.