.png){kind=icon}
Return
Continuous-Time Coordination Algorithm for Distributed Convex Optimization Over Weight-Unbalanced Directed Networks
.png){kind=icon}
OA
AI
DOI：10.1109/TCSII.2018.2878250.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A distributed convex optimization problem over a weight-unbalanced directed network is studied in this brief, where the global objective function is equal to the sum of strongly convex objective functions with globally Lipschitz gradients. With respect to the optimization problem, a new continuous-time coordination algorithm is proposed to compute its optimal solution in a distributed manner. The asymptotical convergence of the proposed algorithm is guaranteed by resorting to the direct sum decomposition technique, Kronecker matrix algebra, the stability of perturbed systems, and input-to-state stability. Finally, some simulations are performed to illustrate the theoretical result.
Keywords:
Distributed convex optimization
continuous-time coordination algorithm
directed network
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
4.9
Papers:
8.8K
Citations:
2.5W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveDistributed Finite-Time Computation of Digraph Parameters: Left-Eigenvector, Out-Degree and Spectrum
PREAI
ShareSave
View more