Name
Abstract | ||
|---|---|---|
Most models of Bidirectional Associative Memories intend to achieve that all trained patterns correspond to stable states; however, this has not been possible. Also, none of the former models has been able to recall all the trained patterns. A new model which appeared recently, called Alpha-Beta Bidirectional Associative Memory (BAM), recalls 100% of the trained patterns, without error. Also, the model is non iterative and has no stability problems. In this work the analysis of time and space complexity of the Alpha-Beta BAM is presented. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11925231_34 | MICAI |
Keywords | DocType | Volume |
alpha-beta bidirectional associative memory,former model,non iterative,stability problem,bidirectional associative memories,new model,alpha-beta bam,trained pattern,stable state,space complexity,bidirectional associative memory | Conference | 4293 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-49026-4 | 1 |
PageRank | References | Authors |
0.35 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| María Elena Acevedo-Mosqueda | 1 | 20 | 2.63 |
| Cornelio Yáñez-Márquez | 2 | 153 | 26.34 |
| Itzamá López-Yáñez | 3 | 78 | 11.76 |