Name
Abstract | ||
|---|---|---|
This paper presents rigorous mathematical proofs for some observed convergence phenomena in an associative memory model introduced by Hopfield (based on Hebbian rules) for storing a number of random n-bit patterns. The capability of the model to correct a linear number of random errors in a bit pattern has been established earlier, but the existence of a large domain of attraction (correcting a linear number of arbitrary errors) has not been proved. |
Year | DOI | Venue |
|---|---|---|
1988 | 10.1016/0893-6080(88)90029-9 | Neural Networks |
Keywords | Field | DocType |
Neural networks,Associative memory,Content addressable memory,Dynamical systems,Spin-glass model,Random quadratic forms,Learning algorithms,Threshold decoding | Convergence (routing),Log-log plot,Discrete mathematics,Binary logarithm,Content-addressable memory,Exponential function,Hebbian theory,Dynamical systems theory,Artificial intelligence,Artificial neural network,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
1 | 3 | 0893-6080 |
Citations | PageRank | References |
39 | 10.37 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| János Komlós | 1 | 1254 | 255.25 |
| Ramamohan Paturi | 2 | 1260 | 92.20 |