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IPSN
2004
Springer
14 years 25 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
JMLR
2011
187views more  JMLR 2011»
13 years 2 months ago
Robust Statistics for Describing Causality in Multivariate Time Series
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Florin Popescu
DAGSTUHL
2010
13 years 9 months ago
Visual Simulation of Flow
We have adopted a numerical method from computational fluid dynamics, the Lattice Boltzmann Method (LBM), for real-time simulation and visualization of flow and amorphous phenomen...
Arie E. Kaufman, Ye Zhao
ICRA
2006
IEEE
113views Robotics» more  ICRA 2006»
14 years 1 months ago
Integration of Dependent Bayesian Filters for Robust Tracking
— Robotics applications based on computer vision algorithms are highly constrained to indoor environments where conditions may be controlled. The development of robust visual alg...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
TEC
2008
93views more  TEC 2008»
13 years 7 months ago
The Self-Organization of Interaction Networks for Nature-Inspired Optimization
Over the last decade, significant progress has been made in understanding complex biological systems, however there have been few attempts at incorporating this knowledge into natu...
James M. Whitacre, Ruhul A. Sarker, Q. Tuan Pham