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AUTOMATICA
2006
132views more  AUTOMATICA 2006»
13 years 8 months ago
A new autocovariance least-squares method for estimating noise covariances
Industrial implementation of model-based control methods, such as model predictive control, is often complicated by the lack of knowledge about the disturbances entering the syste...
Brian J. Odelson, Murali R. Rajamani, James B. Raw...
ICASSP
2009
IEEE
14 years 3 months ago
On the error exponents for detecting randomly sampled noisy diffusion processes
This paper deals with the detection of a continuous random process described by an Ornstein-Uhlenbeck (O-U) stochastic differential equation. Randomly spaced sensors or equivalent...
Walid Hachem, Eric Moulines, Jamal Najim, Fran&cce...
ICIP
2006
IEEE
14 years 2 months ago
Compressive Sampling Vs. Conventional Imaging
Compressive sampling (CS), or “Compressed Sensing,” has recently generated a tremendous amount of excitement in the image processing community. CS involves taking a relatively...
Jarvis Haupt, Robert Nowak
TIT
2011
121views more  TIT 2011»
13 years 3 months ago
Strongly Consistent Estimation of the Sample Distribution of Noisy Continuous-Parameter Fields
The general problem of defining and determining the sample distribution in the case of continuousparameter random fields, is addressed. Defining a distribution in the case of d...
Shahar Z. Kovalsky, Guy Cohen, Joseph M. Francos
ICPR
2008
IEEE
14 years 2 months ago
Weighted solution path algorithm of support vector regression for abnormal data
In the solution path algorithm of support vector regression, the penalty for violation of the required error is considered equally for every training sample, which means every tra...
Wen-tao Mao, Long-lei Dong, Gang Zhang