The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Feedback-error-learning neural network for trajectory control of a robotic manipulator
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Citations
Cites
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
The coordination of arm movements: an experimentally confirmed mathematical model
Flash, T., & Hogan, N. (1985) · The Journal of Neuroscience · doi:10.1523/jneurosci.05-07-01688.1985 · Cited by 4,395
Neuronlike adaptive elements that can solve difficult learning control problems
Barto, A. G., Sutton, R. S., & Anderson, C. W. (1983) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1983.6313077 · Cited by 3,233
The cerebellum and neural control
Ito, M. (1984) · Cited by 2,314
A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)
Albus, J. S. (1975) · Journal of Dynamic Systems, Measurement, and Control · doi:10.1115/1.3426922 · Cited by 2,177
The cerebellum and neural control
Tindall, S. C. (1985) · Surgical Neurology · doi:10.1016/0090-3019(85)90320-9 · Cited by 1,754
On-Line Computational Scheme for Mechanical Manipulators
Luh, J. Y. S., Walker, M. W., & Paul, R. P. C. (1980) · Journal of Dynamic Systems, Measurement, and Control · doi:10.1115/1.3149599 · Cited by 1,585
A hierarchical neural-network model for control and learning of voluntary movement
Kawato, M., Furukawa, K., & Suzuki, R. (1987) · Biological Cybernetics · doi:10.1007/bf00364149 · Cited by 1,573
Self-citationStationary and Nonstationary Learning Characteristics of the LMS Adaptive Filter
Widrow, B., McCool, J., Larimore, M. G., & Johnson, C. R. (1977) · Aspects of Signal Processing · doi:10.1007/978-94-010-1223-2_23 · Cited by 1,195
Cerebrocerebellar communication systems.
Allen, G. I., & Tsukahara, N. (1974) · Physiological Reviews · doi:10.1152/physrev.1974.54.4.957 · Cited by 1,069
Cited by
Model learning for robot control: A survey
Nguyen-Tuong, D., & Peters, J. (2011) · Cognitive Processing · doi:10.1007/s10339-011-0404-1 · Cited by 503
Does the nervous system use equilibrium-point control to guide single and multiple joint movements?
Bizzi, E., Hogan, N., Mussa-Ivaldi, F. A., & Giszter, S. (1992) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00072538 · Cited by 465
Theory and applications of neural networks for industrial control systems
Fukuda, T., & Shibata, T. (1992) · IEEE Transactions on Industrial Electronics · doi:10.1109/41.170966 · Cited by 391
Does the nervous system depend on kinesthetic information to control natural limb movements?
Gandevia, S. C., & Burke, D. (1992) · Behavioral and Brain Sciences · doi:10.1017/s0140525x0007254x · Cited by 359
The representation of egocentric space in the posterior parietal cortex
Stein, J. F. (1992) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00072605 · Cited by 339
Metadata
- Authors
- Miyamoto, H., Kawato, M., Setoyama, T., & Suzuki, R.
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 1988-01
- Volume
- 1
- Issue
- 3
- Pages
- 251-265
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2002410308
- Cited by
- 443
- References
- 26
- FWCI
- 9.35
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Feedback-error-learning neural network for trajectory control of a robotic manipulator. https://app.cochat.ai/papers/10.1016/0893-6080(88)90030-5
- The paper
- Miyamoto, H., Kawato, M., Setoyama, T., & Suzuki, R. (1988). Feedback-error-learning neural network for trajectory control of a robotic manipulator. Neural Networks. https://doi.org/10.1016/0893-6080(88)90030-5
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.
