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AUTOMATICA
2006
140views more  AUTOMATICA 2006»
15 years 7 months ago
On a stochastic sensor selection algorithm with applications in sensor scheduling and sensor coverage
In this note we consider the following problem. Suppose a set of sensors is jointly trying to estimate a process. One sensor takes a measurement at every time step and the measure...
Vijay Gupta, Timothy H. Chung, Babak Hassibi, Rich...
IJHIS
2008
84views more  IJHIS 2008»
15 years 7 months ago
Selective generation of training examples in active meta-learning
Meta-Learning has been successfully applied to acquire knowledge used to support the selection of learning algorithms. Each training example in Meta-Learning (i.e. each meta-exampl...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
CORR
2007
Springer
131views Education» more  CORR 2007»
15 years 7 months ago
Bayesian sequential change diagnosis
Sequential change diagnosis is the joint problem of detection and identification of a sudden and unobservable change in the distribution of a random sequence. In this problem, the...
Savas Dayanik, Christian Goulding, H. Vincent Poor
TCBB
2008
113views more  TCBB 2008»
15 years 7 months ago
Efficient Algorithms for the Computational Design of Optimal Tiling Arrays
The representation of a genome by oligonucleotide probes is a prerequisite for the analysis of many of its basic properties, such as transcription factor binding sites, chromosomal...
Alexander Schliep, Roland Krause
AUTOMATICA
2005
103views more  AUTOMATICA 2005»
15 years 7 months ago
Incorporating state estimation into model predictive control and its application to network traffic control
Model predictive control (MPC) is of interest because it is one of the few control design methods which preserves standard design variables and yet handles constraints. MPC is nor...
Jun Yan, Robert R. Bitmead