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Sensing with Optimal Matrices
Sensing with Optimal Matrices Information Theory
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2012/6/14
We consider the problem of designing optimal $M \times N$ ($M \leq N$) sensing matrices which minimize the maximum condition number of all the submatrices of $K$ columns. Such matrices minimize the wo...
Consensus and Products of Random Stochastic Matrices: Exact Rate for Convergence in Probability
Consensus consensus+innovations performance analysis random network convergence in probability exponential rate
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2012/3/1
Distributed consensus and other linear systems with system stochastic matrices $W_k$ emerge in various settings, like opinion formation in social networks, rendezvous of robots, and distributed infere...
ROBUST KALMAN FILTERING FOR SYSTEMS UNDER NORM BOUNDED UNCERTAINTIES IN ALL SYSTEM MATRICES AND ERROR COVARIANCE CONSTRAINTS
Kalman filtering robust filtering unce
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2007/8/7
This paper concerns robust Kalman filtering for systems undernorm bounded uncertainties in all the system matrices and errorcovariance constraints. Sufficient conditions are given for theexistence of ...