The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Die Lernmatrix
Overview
The claims and statistics of this paper haven’t been checked yet.
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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.
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
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb00917.x · Cited by 48,949
The perceptron: A probabilistic model for information storage and organization in the brain.
Rosenblatt, F. (1958) · Psychological Review · doi:10.1037/h0042519 · Cited by 12,280
Error Detecting and Error Correcting Codes
Hamming, R. W. (1950) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1950.tb00463.x · Cited by 5,377
Mowrer, O. H. (1960) · doi:10.1037/10802-000 · Cited by 1,670
New Phenomenon in Narrow Germaniump−nJunctions
Esaki, L. (1958) · Physical Review · doi:10.1103/physrev.109.603 · Cited by 1,558
(1981) · Comparative Biochemistry and Physiology Part A: Physiology · doi:10.1016/0300-9629(81)93038-3 · Cited by 402
The design of conditional probability computers
Uttley, A. M. (1959) · Information and Control · doi:10.1016/s0019-9958(59)90058-0 · Cited by 44
Cited by
Kohonen, T. (1972) · IEEE Transactions on Computers · doi:10.1109/tc.1972.5008975 · Cited by 885
Gokmen, T., & Vlasov, Y. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00333 · Cited by 491
Palm, G. (1980) · Biological Cybernetics · doi:10.1007/bf00337019 · Cited by 438
Training Deep Convolutional Neural Networks with Resistive Cross-Point Devices
Gokmen, T., Onen, M., & Haensch, W. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00538 · Cited by 162
The marriage of training and inference for scaled deep learning analog hardware
Gokmen, T., Rasch, M. J., & Haensch, W. (2019) · 2019 IEEE International Electron Devices Meeting (IEDM) · doi:10.1109/iedm19573.2019.8993573 · Cited by 37
Metadata
- Authors
- Steinbuch, K.
- Venue
- Kybernetik
- Published
- 1961-01
- Volume
- 1
- Issue
- 1
- Pages
- 36-45
- ISSN
- 0023-5946 (ISSN-L)
- OpenAlex
- W4240778903
- Cited by
- 325
- References
- 7
- FWCI
- 9.35
- Type
- journal article
- Language
- de
- 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 ›
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Die Lernmatrix. https://app.cochat.ai/papers/10.1007/bf00293853
- The paper
- Steinbuch, K. (1961). Die Lernmatrix. Kybernetik. https://doi.org/10.1007/bf00293853
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.
