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A New Approach to Linear Filtering and Prediction Problems
A New Approach Linear Filtering Prediction Problems
2014/8/13
The classical filtering and prediction problem is re-examined using the BodeShannon representation of random processes and the “state transition” method of
analysis of dynamic systems.
A New Approach to Linear Filtering and Prediction Problems
A New Approach Linear Filtering Prediction Problems
2014/7/2
The classical filtering and prediction problem is re-examined using the Bode- Shannon representation of random processes and the “state transition” method of analysis of dynamic systems.
SMART FILTERING OF INTERFEROMETRIC PHASES FOR ENHANCING BUILDING RECONSTRUCTION
Remote Sensing Building Reconstruction High Resolution InSAR
2014/5/8
The current generation of space borne high resolution SAR sensors provides high spatial resolution as well as interferometric data within short time frames. This makes such data attractive for 3D info...
Realizable Rate Distortion Function and Bayesian FIltering Theory
Realizable Rate Distortion Function Bayesian FIltering Theory Information Theory
2012/4/16
The relation between rate distortion function (RDF) and Bayesian filtering theory is discussed. The relation is established by imposing a causal or realizability constraint on the reconstruction condi...
ROBUST KALMAN FILTERING FOR SYSTEMS UNDER NORM BOUNDED UNCERTAINTIES IN ALL SYSTEM MATRICES AND ERROR COVARIANCE CONSTRAINTS
Kalman filtering robust filtering unce
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 ...