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» Asymptotically Optimal Model Estimation for Quantization
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IPSN
2004
Springer
14 years 26 days 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
ESSMAC
2003
Springer
14 years 21 days ago
Joint Optimization of Wireless Communication and Networked Control Systems
Abstract. We consider a linear system, such as an estimator or a controller, in which several signals are transmitted over wireless communication channels. With the coding and medi...
Lin Xiao, Mikael Johansson, Haitham A. Hindi, Step...
BMCBI
2010
97views more  BMCBI 2010»
13 years 4 months ago
Preprocessing of gene expression data by optimally robust estimators
Background: The preprocessing of gene expression data obtained from several platforms routinely includes the aggregation of multiple raw signal intensities to one expression value...
Matthias Kohl, Hans-Peter Deigner
MA
2010
Springer
132views Communications» more  MA 2010»
13 years 5 months ago
Model selection by sequentially normalized least squares
Model selection by the predictive least squares (PLS) principle has been thoroughly studied in the context of regression model selection and autoregressive (AR) model order estima...
Jorma Rissanen, Teemu Roos, Petri Myllymäki
WSC
2004
13 years 8 months ago
Adaptive Control Variates
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...
Sujin Kim, Shane G. Henderson