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» Optimal filtering for uncertain linear stochastic systems
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ICASSP
2010
IEEE
13 years 8 months ago
Empirical Type-i filter design for image interpolation
Empirical filter designs generalize relationships inferred from training data to effect realistic solutions that conform well to the human visual system. Complex algorithms invol...
Karl S. Ni, Truong Q. Nguyen
IJCV
2008
188views more  IJCV 2008»
13 years 8 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin
ICRA
2007
IEEE
168views Robotics» more  ICRA 2007»
14 years 2 months ago
A Multi-State Constraint Kalman Filter for Vision-aided Inertial Navigation
— In this paper, we present an Extended Kalman Filter (EKF)-based algorithm for real-time vision-aided inertial navigation. The primary contribution of this work is the derivatio...
Anastasios I. Mourikis, Stergios I. Roumeliotis
CDC
2009
IEEE
134views Control Systems» more  CDC 2009»
14 years 1 months ago
On LQG joint optimal scheduling and control under communication constraints
Abstract— In this paper, we consider a discrete-time stochastic system, where sensor measurements are sent over a network to the controller. The design objective is a non-classic...
Adam Molin, Sandra Hirche
CDC
2009
IEEE
106views Control Systems» more  CDC 2009»
14 years 1 months ago
Gradient methods for iterative distributed control synthesis
— In this paper we present a gradient method to iteratively update local controllers of a distributed linear system driven by stochastic disturbances. The control objective is to...
Karl Martensson, Anders Rantzer