Name
Abstract | ||
|---|---|---|
A geometrical expansion learning algorithm for multilayer neural networks using unipolar binary neurons with integer connection weights, which guarantees convergence for any Boolean function, is introduced. Neurons in the hidden layer develop as necessary without supervision. In addition, the computational amount is much less than that of the backpropagation algorithm. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1109/12.238491 | IEEE Trans. Computers |
Keywords | Field | DocType |
Boolean functions,feedforward neural nets,learning (artificial intelligence),Boolean function,binary field,geometrical learning algorithm,hidden layer,integer connection weights,multilayer neural networks,unipolar binary neurons | Boolean function,Convergence (routing),Integer,Computer science,Binary fields,Algorithm,Artificial intelligence,Artificial neural network,Backpropagation,Binary number | Journal |
Volume | Issue | ISSN |
42 | 8 | 0018-9340 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. K. Park | 1 | 13 | 4.63 |
| J. H. Kim | 2 | 53 | 10.46 |