Method, system, and computer program product to employ a multi-layered neural network for classification
US11537840B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 13, 2018 |
| Grant date | Dec 27, 2022 |
| Priority date | — |
| Expiry date | May 24, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A neural network classifies an input signal. For example, an accelerometer signal may be classified to detect human activity. In a first convolutional layer, two-valued weights are applied to the input signal. In a first two-valued function layer coupled at input to an output of the first convolutional layer, a two-valued function is applied. In a second convolutional layer coupled at input to an output of the first two-valued functional layer, weights of the second convolutional layer are applied. In a fully-connected layer coupled at input to an output of the second convolutional layer, two-valued weights of the fully connected layer are applied. In a second two-valued function layer coupled at input to an output of the fully connected layer, a two-valued function of the second two-valued function layer is applied. A classifier classifies the input signal based on an output signal of second two-valued function layer.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.