On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\infty}$ Control
- DOI
- 10.1109/tnnls.2016.2642128
- Published
- 2018-04
- Container
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2016.2642128,
title = {On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear \$H\_\{\textbackslash{}infty\}\$ Control},
author = {Ding Wang and Chaoxu Mu and Derong Liu and Hongwen Ma},
year = {2018},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
doi = {10.1109/tnnls.2016.2642128},
url = {https://doi.org/10.1109/tnnls.2016.2642128}
}RIS
TY - JOUR
TI - On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\infty}$ Control
AU - Ding Wang
AU - Chaoxu Mu
AU - Derong Liu
AU - Hongwen Ma
PY - 2018
JO - IEEE Transactions on Neural Networks and Learning Systems
DO - 10.1109/tnnls.2016.2642128
UR - https://doi.org/10.1109/tnnls.2016.2642128
ER - APA
Wang, D., Mu, C., Liu, D., & Ma, H. (2018). On Mixed Data and Event Driven Design for Adaptive-Critic-Based Nonlinear $H_{\infty}$ Control. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2016.2642128
Source records
- crossref · retrieved 2026-11-04T13:13:18.107Z