System and machine learning method for separating noise and signal in multitouch sensors
US12326996B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 8, 2024 |
| Grant date | Jun 10, 2025 |
| Priority date | — |
| Expiry date | Apr 8, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In some examples, touch data can include noise. Machine learning techniques, such as gated recurrent units and convolutional neural networks can be used to mitigate noise present in touch data. 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. The gated recurrent unit can remove noise caused by a first component of the electronic device and the convolutional neural network can remove noise caused by a second component of the electronic device, for example. Thus, together, the gated recurrent unit and the convolutional neural network can remove or substantially reduce the noise in the touch data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.