Single-layered linear neural network based on cell synapse structure
US12373679B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Aug 7, 2019 |
| Grant date | Jul 29, 2025 |
| Priority date | — |
| Expiry date | Mar 25, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/088
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A single-layered linear neural network based on a cell synapse structure comprising a pre-synapse and a post-synapse, the pre-synapse comprises a plurality of precursor resistors, number of the precursor resistors is m, one end of the precursor resistors in the pre-synapse is jointly connected with an intermediate point, and another end of the precursor resistors is respectively connected with each of a plurality of precursor signal input ends, number of the precursor signal input ends is m; the precursor signal input ends are used for receiving input voltages; the post-synapse comprises a plurality of posterior resistors, number of the precursor resistors is n, one end of the posterior resistors in the post-synapse is jointly connected with the intermediate point, and another end of the posterior resistors is respectively connected with each of a plurality of posterior signal output ends, number of the posterior signal output ends is n; the posterior signal output ends are used for outputting currents. The invention provides a single-layered linear neural network based on cell synapse structure, which can reduce the number of resistors; in addition, a weight between an external pr…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.