Machine learning method and system for suppressing display induced noise in touch sensors using information from display circuitry
US11899881B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 15, 2020 |
| Grant date | Feb 13, 2024 |
| Priority date | — |
| Expiry date | Jun 4, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F3/0446
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In some examples, touch data can include noise. The noise can be generated by a component of an electronic device that includes a touch screen. For example, one or more signals transmitted to the display circuitry of an electronic device can become capacitively coupled to the touch circuitry of the device and cause noise in the touch data. Machine learning techniques, such as gated recurrent units and/or convolutional neural networks can estimate and reduce or remove noise from touch data when provided data or information about the displayed image as input. In some examples, the algorithm includes one or more of a gated recurrent unit stage and a convolutional neural network stage. In some examples, a gated recurrent unit stage and a convolutional neural network stage can be arranged in series, such as by providing the output of the gated recurrent unit as input to the convolutional neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.