Spiking neural network for probabilistic computation
US11449735B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 20, 2019 |
| Grant date | Sep 20, 2022 |
| Priority date | — |
| Expiry date | Mar 15, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described is a system for computing conditional probabilities of random variables for Bayesian inference. The system implements a spiking neural network of neurons to compute the conditional probability of two random variables X and Y. The spiking neural network includes an increment path for a synaptic weight that is proportional to a product of the synaptic weight and a probability of X, a decrement path for the synaptic weight that is proportional to a probability of X, Y, and delay and spike timing dependent plasticity (STDP) parameters such that the synaptic weight increases and decreases with the same magnitude for a single firing event.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.