Name
Abstract | ||
|---|---|---|
The problem of binary factorization of complex patterns in recurrent Hopfield-like neural network was studied by means of computer simulation. The network ability to perform a factorization was analyzed depending on the number and sparseness of factors mixed in presented patterns. Binary factorization in sparsely encoded Hopfield-like neural network is treated as efficient statistical method and as a functional model of hippocampal CA3 field. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1007/978-3-642-57489-4_22 | COMPSTAT 2002: PROCEEDINGS IN COMPUTATIONAL STATISTICS |
Keywords | DocType | Citations |
binary factorization, Hopfield network, sparse encoding | Conference | 3 |
PageRank | References | Authors |
1.18 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| D. Husek | 1 | 3 | 1.18 |
| A. A. Frolov | 2 | 4 | 1.56 |
| Hana Rezanková | 3 | 56 | 9.79 |
| Václav Snasel | 4 | 1261 | 210.53 |