Dynamically stable associative learning neural network system
US5588091A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Mar 2, 1995 |
| Grant date | Dec 24, 1996 |
| Priority date | — |
| Expiry date | Mar 2, 2015 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/454
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A dynamically stable associative learning neural network system includes, in its basic architectural unit, at least one each of a conditioned signal input, an unconditioned signal input and an output. Interposed between input and output elements are "patches," or storage areas of dynamic interaction between conditioned and unconditioned signals which process information to achieve associative learning locally under rules designed for application-related goals of the system. Patches may be fixed or variable in size. Adjustments to a patch radius may be by "pruning" or "budding." The neural network is taught by successive application of training sets of input signals to the input terminals until a dynamic equilibrium is reached. Enhancements and expansions of the basic unit result in multilayered (multi-subnetworked) systems having increased capabilities for complex pattern classification and feature recognition.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.