Backpropagation of errors in pulsed form in a pulsed neural network
US12147902B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 22, 2019 |
| Grant date | Nov 19, 2024 |
| Priority date | — |
| Expiry date | Mar 13, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A new implementation is provided for an error back-propagation algorithm that is suited to the hardware constraints of a device implementing a spiking neural network. The invention notably uses binary or ternary encoding of the errors calculated in the back-propagation phase to adapt its implementation to the constraints of the network, and thus to avoid having to use floating-point number multiplication operators. More generally, the invention proposes a global adaptation of the back-propagation algorithm to the specific constraints of a spiking neural network. In particular, the invention makes it possible to use the same propagation infrastructure to propagate the data and to back-propagate the errors in the training phase. The invention proposes a generic implementation of a spiking neuron that is suitable for implementing any type of spiking neural network, in particular convolutional networks.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.