Method and circuits for associating a complex operator to each component of an input pattern presented to an artificial neural network
US8027942B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 12, 2001 |
| Grant date | Sep 27, 2011 |
| Priority date | — |
| Expiry date | Jul 2, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/24147
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The method and circuits of the present invention aim to associate a complex component operator (CC_op) to each component of an input pattern presented to an input space mapping algorithm based artificial neural network (ANN) during the distance evaluation process. A complex operator consists in the description of a function and a set of parameters attached thereto. The function is a mathematical entity (either a logic operator e.g. match(Ai,Bi), abs(Ai−Bi), . . . or an arithmetic operator, e.g. >, <, . . . ) or a set of software instructions possibly with a condition. In a first embodiment, the ANN is provided with a global memory, common for all the neurons of the ANN, that stores all the CC_ops. In another embodiment, the set of CC_ops is stored in the prototype memory of the neuron, so that the global memory is no longer physically necessary. According to the present invention, a component of a stored prototype may now designate objects of different nature. In addition, either implementation significantly reduces the number of components that are required in the neurons, therefore saving room when the ANN is integrated in a silicon chip.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.