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2008
101views more  ADHOC 2008»
13 years 10 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
12 years 7 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
14 years 4 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»
14 years 3 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»
14 years 1 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...