The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Information capacity of the Hopfield model
Abstract
The information capacity of general forms of memory is formalized. The number of bits of information that can be stored in the Hopfield model of associative memory is estimated. It is found that the asymptotic information capacity of a Hopfield network ofNneurons is of the orderN^{3}b. The number of arbitrary state vectors that can be made stable in a Hopfield network ofNneurons is proved to be bounded above byN.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“If the learning rule is not related to the Hebb rule, then up to d patterns can be stored (Abu-Mostafa & StJacques, 1985).”
From Hopfield Networks is All You Need (2020) · cites this paper as Abu-Mostafa & StJacques, 1985
In the citing paper
“If the learning rule is not related to the Hebb rule then up to d patterns can be stored (Abu-Mostafa & StJacques, 1985).”
From Hopfield Networks is All You Need (2020) · cites this paper as Abu-Mostafa & StJacques, 1985
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
Cited by
Computing with Neural Circuits: A Model
Hopfield, J. J., & Tank, D. W. (1986) · Science · doi:10.1126/science.3755256 · Cited by 2,116
Progress in supervised neural networks
Hush, D. R., & Horne, B. G. (1993) · IEEE Signal Processing Magazine · doi:10.1109/79.180705 · Cited by 1,247
The capacity of the Hopfield associative memory
McEliece, R., Posner, E., Rodemich, E., & Venkatesh, S. (1987) · IEEE Transactions on Information Theory · doi:10.1109/tit.1987.1057328 · Cited by 910
Fuzzy entropy and conditioning
Kosko, B. (1986) · Information Sciences · doi:10.1016/0020-0255(86)90006-x · Cited by 621
A theoretical investigation into the performance of the Hopfield model
Aiyer, S. V. B., Niranjan, M., & Fallside, F. (1990) · IEEE Transactions on Neural Networks · doi:10.1109/72.80232 · Cited by 381
Metadata
- Authors
- Abu-Mostafa, Y., & St. Jacques, J.
- Venue
- IEEE Transactions on Information Theory
- Published
- 1985-07
- Volume
- 31
- Issue
- 4
- Pages
- 461-464
- ISSN
- 0018-9448 (ISSN-L)
- 1557-9654
- OpenAlex
- W2059146732
- Cited by
- 267
- References
- 1
- FWCI
- 12.79
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Information capacity of the Hopfield model. https://app.cochat.ai/papers/10.1109/tit.1985.1057069
- The paper
- Abu-Mostafa, Y., & St. Jacques, J. (1985). Information capacity of the Hopfield model. IEEE Transactions on Information Theory. https://doi.org/10.1109/tit.1985.1057069
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
