Reference : Distributed reconstruction of nonlinear networks: An ADMM approach
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Multidisciplinary, general & others
http://hdl.handle.net/10993/21011
Distributed reconstruction of nonlinear networks: An ADMM approach
English
Pan, Wei mailto []
Sootla, Aivar []
Stan, Guy-Bart []
2014
Proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC 2014)
International Federation of Automatic Control
19
Yes
978-3-902823-62-5
19th World Congress of the International Federation of Automatic Control (IFAC 2014)
24 - 29 August, 2014
Cape Town
South Africa
[en] In this paper, we present a distributed algorithm for the reconstruction of large-scale nonlinear networks. In particular, we focus on the identification from time-series data of the nonlinear functional forms and associated parameters of large-scale nonlinear networks. In (Pan et al. (2013)), a nonlinear network reconstruction problem was formulated as a nonconvex optimisation problem based on the combination of a marginal likelihood maximisation procedure with sparsity inducing priors. Using a convex-concave procedure (CCCP), an iterative reweighted lasso algorithm was derived to solve the initial nonconvex optimisation problem. By exploiting the structure of the objective function of this reweighted lasso algorithm, a distributed algorithm can be designed. To this end, we apply the alternating direction method of multipliers (ADMM) to decompose the original problem into several subproblems. To illustrate the effectiveness of the proposed methods, we use our approach to identify a network of interconnected Kuramoto oscillators with different network sizes (500∼100,000 nodes).
http://hdl.handle.net/10993/21011
http://arxiv.org/pdf/1403.7429v1.pdf

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