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Hopfield learning rule with high capacity storage of time-correlated patterns
| Content Provider | Semantic Scholar |
|---|---|
| Author | Storkey, Amos J. Valabrègue, Romain |
| Copyright Year | 1997 |
| Abstract | A new local and incremental learning rule is examined for its ability to store patterns from a time series in an attractor neural network. This learning rule has a higher capacity than the Hebb rule, and suffers significantly less capacity loss as the correlation between patterns increases. |
| Starting Page | 1803 |
| Ending Page | 1804 |
| Page Count | 2 |
| File Format | PDF HTM / HTML |
| DOI | 10.1049/el:19971233 |
| Volume Number | 33 |
| Alternate Webpage(s) | http://www.anc.ed.ac.uk/~amos/correl.ps.gz |
| Alternate Webpage(s) | https://www.research.ed.ac.uk/portal/files/20036741/Storkey_Valabregue_1994_A_Hopefield_learning_rule.pdf |
| Alternate Webpage(s) | https://doi.org/10.1049/el%3A19971233 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |