NDLI: Topology identification of a sparse dynamic network

Content Provider	IEEE Xplore Digital Library
Author	Seneviratne, A.J. Solo, V.
Copyright Year	2012
Description	Author affiliation: School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, Australia (Seneviratne, A.J.; Solo, V.)
Abstract	This paper addresses the problem of identifying the topology of a sparsely connected network of dynamic systems. The goal is to identify the links, the direction of information flow and the transfer function of each dynamic system. The output of each system is affected by the incoming data of the directly connected systems and noise. In contrast to the related existing work we use causal Laguerre basis functions to expand the transfer functions. Since the network is sparsely connected we estimate the system topology using an algorithm which optimizes the l0 penalized least squares criterion with grouped variables. This also contrasts with previous work which usually uses and l1 penalty. The l0 penalty has the potential to generate greater sparsity. We present simulation results to demonstrate the effectiveness of this method.
Starting Page	1518
Ending Page	1523
File Size	323380
Page Count	6
File Format	PDF
ISBN	9781467320658
ISSN	07431546
e-ISBN	9781467320665
e-ISBN	9781467320641
DOI	10.1109/CDC.2012.6425980
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time series analysis Network topology Topology Transfer functions Matching pursuit algorithms Conferences Mathematical model
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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