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CDC
2008
IEEE
126views Control Systems» more  CDC 2008»
13 years 7 months ago
Subspace identification using predictor estimation via Gaussian regression
In this paper we propose a new nonparametric approach to identification of linear time invariant systems using subspace methods. The nonparametric paradigm to prediction of station...
Alessandro Chiuso, Gianluigi Pillonetto, Giuseppe ...
IPSN
2004
Springer
13 years 11 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
CDC
2008
IEEE
154views Control Systems» more  CDC 2008»
14 years 7 days ago
Distributed calculation of linear functions in noisy networks via linear iterations
— Given a fixed network where each node has some given initial value, and under the constraint that each node receives noisy transmissions from its immediate neighbors, we provi...
Shreyas Sundaram, Christoforos N. Hadjicostis
CDC
2009
IEEE
134views Control Systems» more  CDC 2009»
13 years 10 months ago
On LQG joint optimal scheduling and control under communication constraints
Abstract— In this paper, we consider a discrete-time stochastic system, where sensor measurements are sent over a network to the controller. The design objective is a non-classic...
Adam Molin, Sandra Hirche
CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 4 months ago
Learning Networks of Stochastic Differential Equations
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
José Bento, Morteza Ibrahimi, Andrea Montan...