Discriminant neural networks
US5926804A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Jul 1, 1994 |
| Grant date | Jul 20, 1999 |
| Priority date | — |
| Expiry date | Jul 1, 2014 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A discriminant neural network and a method of training the network are disclosed. The network includes a set of hidden nodes having associated weights, and the number of hidden nodes is minimized by the training method of the invention. The training method includes the steps of 1) loading a training data set and assigning it to a residual data set, 2) computing a vector associated with a first hidden node using the residual data set, 3) projecting training data onto a hyperplane associated with said first hidden node, 4) determining the number and locations of hard-limiter thresholds associated with the first node, and 5) repeating the above for successive hidden nodes after removing satisfied subsets from the training data until all partitioned regions of the input data space are satisfied.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.