The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The ART of adaptive pattern recognition by a self-organizing neural network
Abstract
The adaptive resonance theory (ART) suggests a solution to the stability-plasticity dilemma facing designers of learning systems, namely how to design a learning system that will remain plastic, or adaptive, in response to significant events and yet remain stable in response to irrelevant events. ART architectures are discussed that are neural networks that self-organize stable recognition codes in real time in response to arbitrary sequences of input patterns. Within such an ART architecture, the process of adaptive pattern recognition is a special case of the more general cognitive process of hypothesis discovery, testing, search, classification, and learning. This property opens up the possibility of applying ART systems to more general problems of adaptively processing large abstract information sources and databases. The main computational properties of these ART architectures are outlined and contrasted with those of alternative learning and recognition systems.>
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.
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 learning algorithm for Boltzmann machines
Ackley, D. H., Hinton, G. E., & Sejnowski, T. J. (1985) · Cognitive Science · doi:10.1207/s15516709cog0901_7 · Cited by 3,402
Bienenstock, E., Cooper, L., & Munro, P. (1982) · The Journal of Neuroscience · doi:10.1523/jneurosci.02-01-00032.1982 · Cited by 2,896
A massively parallel architecture for a self-organizing neural pattern recognition machine
Carpenter, G. A., & Grossberg, S. (1987) · Computer Vision, Graphics, and Image Processing · doi:10.1016/s0734-189x(87)80014-2 · Cited by 2,525
Self-citation
Cited by
Twitter mood predicts the stock market
Bollen, J., Mao, H., & Zeng, X. (2011) · Journal of Computational Science · doi:10.1016/j.jocs.2010.12.007 · Cited by 5,206
A Comprehensive Survey of Clustering Algorithms
Xu, D., & Tian, Y. (2015) · Annals of Data Science · doi:10.1007/s40745-015-0040-1 · Cited by 1,939
Machine learning in manufacturing: Advantages, challenges, and applications
Wuest, T., Weimer, D., Irgens, C., & Thoben, K.-D. (2016) · Production & Manufacturing Research · doi:10.1080/21693277.2016.1192517 · Cited by 1,319
Catastrophic forgetting, rehearsal and pseudorehearsal
ROBINS, A. (1995) · Connection Science · doi:10.1080/09540099550039318 · Cited by 833
System consolidation of memory during sleep
Born, J., & Wilhelm, I. (2012) · Psychological Research · doi:10.1007/s00426-011-0335-6 · Cited by 667
Metadata
- Authors
- Carpenter, G. A., & Grossberg, S.
- Venue
- Computer
- Published
- 1988-03
- Volume
- 21
- Issue
- 3
- Pages
- 77-88
- ISSN
- 0018-9162 (ISSN-L)
- DOI
- 10.1109/2.33
- OpenAlex
- W2106304233
- Cited by
- 1,287
- References
- 3
- FWCI
- 43.49
- 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: The ART of adaptive pattern recognition by a self-organizing neural network. https://app.cochat.ai/papers/10.1109/2.33
- The paper
- Carpenter, G. A., & Grossberg, S. (1988). The ART of adaptive pattern recognition by a self-organizing neural network. Computer. https://doi.org/10.1109/2.33
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.
