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Cited by 342

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

Neural Model of Adaptive Hand-Eye Coordination for Single Postures

Kuperstein, Michael·1988·Science
DOI 10.1126/science.3344437
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Abstract

A neural network model has been developed that achieves adaptive visual-motor coordination of a multijoint arm, without a teacher. The model learns to position an arm so that it reaches a cylinder arbitrarily positioned in space. The model uses a new neural architecture and a new algorithm for modifying neural-connection strengths. Computer simulations show that the model performs with an average position error of 4% of the arm's length and with an average orientation error of 4°. The model is designed to be generalized for coordinating any number of topographic sensory inputs with limbs of any number of joints.

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Crossref · 10.1126/science.3344437

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Metadata

Authors
Kuperstein, M.
Venue
Science
Publisher
American Association for the Advancement of Science (AAAS)
Published
1988-03-11
Volume
239
Issue
4845
Pages
1308-1311
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
DOI
10.1126/science.3344437
OpenAlex
W1997508571
Cited by
342
References
13
FWCI
11.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Neural Model of Adaptive Hand-Eye Coordination for Single Postures. https://app.cochat.ai/papers/10.1126/science.3344437
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Kuperstein, M. (1988). Neural Model of Adaptive Hand-Eye Coordination for Single Postures. Science. https://doi.org/10.1126/science.3344437

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.