Receptive field neural network with shift-invariant pattern recognition
US5263107A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Jan 31, 1991 |
| Grant date | Nov 16, 1993 |
| Priority date | — |
| Expiry date | Jan 31, 2011 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V30/287
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A neural network system and method of operating same wherein input data are initialized, then mapped onto a predetermined array for learning or recognition. The mapped information is divided into sub-input data or receptive fields, which are used for comparison of the input information with prelearned information having similar features, thereby allowing for correct classification of the input information. The receptive fields are shifted before the classification process, in order to generate a closest match between features which may be shifted at the time of input, and weights of the input information are updated based upon the closest-matching shifted position of the input information.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.