0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessThe last decade has seen an explosion of research in network controllability. The present article reviews some basic concepts, significant progress, important results and recent advances in the studies of the controllability of networked linear dynamical systems, regarding the relationship of the network topology, node-system dynamics, external control inputs and inner dynamical interactions with the controllability of such complex networked dynamical systems. Different approaches to analyzing the network controllability are evaluated. Some advanced topics on the selection of driver nodes, optimization of network controllability and control energy are discussed. Potential applications to real-world networked systems are also described. Finally, a near-future research outlook is highlighted.
Linying Xiang, Fei Chen, Wei Ren, Guanrong Chen (2019). Advances in Network Controllability. IEEE Circuits and Systems Magazine, 19(2), pp. 8-32, DOI: 10.1109/mcas.2019.2909446.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2019
Authors
4
Datasets
0
Total Files
0
Language
English
Journal
IEEE Circuits and Systems Magazine
DOI
10.1109/mcas.2019.2909446
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access
