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2008
101views more  ADHOC 2008»
15 years 5 months ago
Monte Carlo localization for mobile wireless sensor networks
Localization is crucial to many applications in wireless sensor networks. In this article, we propose a range-free anchorbased localization algorithm for mobile wireless sensor ne...
Aline Baggio, Koen Langendoen
CVPR
2010
IEEE
14 years 2 months ago
Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling
Robust tracking of abrupt motion is a challenging task in computer vision due to the large motion uncertainty. In this paper, we propose a stochastic approximation Monte Carlo (...
Xiuzhuang Zhou and Yao Lu
CISS
2008
IEEE
15 years 11 months ago
Near optimal lossy source coding and compression-based denoising via Markov chain Monte Carlo
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
Shirin Jalali, Tsachy Weissman
ICRA
2005
IEEE
150views Robotics» more  ICRA 2005»
15 years 10 months ago
Learning Sensor Network Topology through Monte Carlo Expectation Maximization
— We consider the problem of inferring sensor positions and a topological (i.e. qualitative) map of an environment given a set of cameras with non-overlapping fields of view. In...
Dimitri Marinakis, Gregory Dudek, David J. Fleet
ASPDAC
2007
ACM
133views Hardware» more  ASPDAC 2007»
15 years 9 months ago
Modeling Sub-90nm On-Chip Variation Using Monte Carlo Method for DFM
- For sub-90nm technology nodes and below, random fluctuations of within-die physical process properties are also known as random on-chip variation (OCV). It impacts on the VLSI/So...
Jun-Fu Huang, Victor C. Y. Chang, Sally Liu, Kelvi...