Neural system of classification and classification method using such a system
US5175796A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Apr 12, 1991 |
| Grant date | Dec 29, 1992 |
| Priority date | — |
| Expiry date | Apr 12, 2011 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosure concerns neural networks designed specially for the classification of objects represented by vectors X. If the vectors X include several parameters and if the objects have to be classified in a large number N of classes, the end result is a very large number of interconnections which become difficult to set up physically, are slow in their operation and require lengthy learning phases. The disclosed neural classification system has the particular feature of being constituted on the basis of P neural networks each individually carrying out the classification of objects in only two classes or, at any rate, in a small number of classes only. These networks give probabilities P.sub.i,j of membership in a class C.sub.i among two classes C.sub.i and C.sub.j. The outputs of these networks are connected to a signal processing module which, through simple functions (implementing linear combinations of the outputs and non-linear standardization functions) establishes, on N outputs, results P.sub.i (X) of classification among the N classes. The learning is done on classifications by pairs of classes, but the post-learning recognition gives classifications among N classes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.