Nana Yang
Orcid: 0000-0001-9498-217X
According to our database1,
Nana Yang
authored at least 18 papers
between 2013 and 2024.
Collaborative distances:
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Bibliography
2024
How does industrial coagglomeration affect regional green innovation? Evidence from Chinese cities.
Technol. Anal. Strateg. Manag., January, 2024
2023
Divalent Aptamer-Functionalized Nanochannels for Facile Detection of Cancer Cell-Derived Exosomes.
Sensors, November, 2023
Does Industrial Agglomeration Promote Regional Innovation Convergence in China? Evidence From High-Tech Industries.
IEEE Trans. Engineering Management, April, 2023
2022
The interaction effects of GVC involvement and domestic R&D on carbon emissions: evidence from China's industrial sectors.
Technol. Anal. Strateg. Manag., 2022
J. Electr. Comput. Eng., 2022
Performance analysis of cooperative cognitive radio networks based on hybrid NOMA/OMA and best relay selection.
IET Commun., 2022
Modelling Analysis of a Novel Frameless Slotted-ALOHA Protocol Based on the Number of Detectable Conflicting Users.
Future Internet, 2022
Distributed Coordination for a Class of High-Order Multiagent Systems Subject to Actuator Saturations by Iterative Learning Control.
Complex., 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022
2021
IEEE Access, 2021
2020
Global value chain, industrial agglomeration and innovation performance in developing countries: insights from China's manufacturing industries.
Technol. Anal. Strateg. Manag., 2020
Completely distributed neuro-learning consensus with position constraints and partially unknown control directions.
Neurocomputing, 2020
Fully distributed hybrid adaptive learning consensus protocols for a class of non-linearly parameterized multi-agent systems.
Appl. Math. Comput., 2020
Distributed Robust Adaptive Learning Coordination Control for High-Order Nonlinear Multi-Agent Systems With Input Saturation.
IEEE Access, 2020
2019
Sensors, 2019
New distributed adaptive protocols for uncertain nonlinear leader-follower multi-agent systems via a repetitive learning control approach.
J. Frankl. Inst., 2019
2013
Proceedings of the Intelligence Science and Big Data Engineering, 2013