Resilient neural network
US12380320B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 18, 2019 |
| Grant date | Aug 5, 2025 |
| Priority date | — |
| Expiry date | Sep 15, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention discloses a spiking neural network for classifying input signals. The spiking neural network comprises a plurality of spiking neurons, and a plurality of synaptic elements interconnecting the spiking neurons to form the network. Each synaptic element is adapted to receive a synaptic input signal and apply a weight to the synaptic input signal to generate a synaptic output signal, the synaptic elements being configurable to adjust the weight applied by each synaptic element. Furthermore, each of the spiking neurons is adapted to receive one or more of the synaptic output signals from one or more of the synaptic elements, and generate a spatio-temporal spike train output signal in response to the received one or more synaptic output signals. The spiking neural network is partitioned into multiple sub-networks, wherein each sub-network comprises a sub-set of the spiking neurons connected to receive synaptic output signals from a sub-set of the synaptic elements. The sub-network is adapted to generate a sub-network output pattern signal in response to a sub-network input pattern signal applied to the sub-network. Furthermore, each sub-network forms part of one or …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.