Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models
Abstract
The information capacity of Kanerva's Sparse, Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the to(cid:173) tal information stored in these systems is proportional to the number connections in the net(cid:173) work. The proportionality constant is the same for the SDM and HopJreld-type models in(cid:173) dependent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store se(cid:173) quences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.
Cite
Text
Keeler. "Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models." Neural Information Processing Systems, 1987.Markdown
[Keeler. "Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models." Neural Information Processing Systems, 1987.](https://mlanthology.org/neurips/1987/keeler1987neurips-capacity/)BibTeX
@inproceedings{keeler1987neurips-capacity,
title = {{Capacity for Patterns and Sequences in Kanerva's SDM as Compared to Other Associative Memory Models}},
author = {Keeler, James D.},
booktitle = {Neural Information Processing Systems},
year = {1987},
pages = {412-421},
url = {https://mlanthology.org/neurips/1987/keeler1987neurips-capacity/}
}