Name
Abstract | ||
|---|---|---|
The Lernmatrix, which is the first known model of associative memory, is a hetereoassociative memory that presents the problem of incorrect pattern recall, even in the fundamental set, depending on the associations. In this work we propose a new algorithm and the corresponding theoretical support to improve the recalling capacity of the original model. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72393-6_100 | ISNN (2) |
Keywords | Field | DocType |
original model,hetereoassociative memory,fundamental set,corresponding theoretical support,new algorithm,known model,incorrect pattern recall,associative memory | Content-addressable memory,Bidirectional associative memory,Computer science,Artificial intelligence,Lernmatrix,Recall,Machine learning | Conference |
Volume | ISSN | Citations |
4492 | 0302-9743 | 1 |
PageRank | References | Authors |
0.38 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Israel Román-Godínez | 1 | 4 | 1.12 |
| Itzamá López-Yáñez | 2 | 78 | 11.76 |
| Cornelio Yáñez-Márquez | 3 | 153 | 26.34 |