Learning neural networks of programmable device blocks directly with backpropagation
US12067484B2 · kind B2 · utility
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Key dates
| Filing date | Jun 21, 2019 |
| Grant date | Aug 20, 2024 |
| Priority date | — |
| Expiry date | Mar 18, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An example method of training a neural network includes defining hardware building blocks (HBBs), neuron equivalents (NEQs), and conversion procedures from NEQs to HBBs; defining the neural network using the NEQs in a machine learning framework; training the neural network on a training platform; and converting the neural network as trained into a netlist of HBBs using the conversion procedures to convert the NEQs in the neural network to the HBBs of the netlist.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.