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» The Value of Observation for Monitoring Dynamic Systems
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NIPS
1998
15 years 1 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
CORR
2006
Springer
113views Education» more  CORR 2006»
14 years 12 months ago
Decentralized Maximum Likelihood Estimation for Sensor Networks Composed of Nonlinearly Coupled Dynamical Systems
Abstract--In this paper, we propose a decentralized sensor network scheme capable to reach a globally optimum maximum-likelihood (ML) estimate through self-synchronization of nonli...
Sergio Barbarossa, Gesualdo Scutari
CORR
2010
Springer
102views Education» more  CORR 2010»
14 years 12 months ago
Stable Takens' Embeddings for Linear Dynamical Systems
Takens' Embedding Theorem remarkably established that concatenating M previous outputs of a dynamical system into a vector (called a delay coordinate map) can be a one-to-one...
Han Lun Yap, Christopher J. Rozell
AUTOMATICA
2005
152views more  AUTOMATICA 2005»
14 years 11 months ago
Identification of dynamical systems with a robust interval fuzzy model
In this paper we present a new method of interval fuzzy model identification. The method combines a fuzzy identification methodology with some ideas from linear programming theory...
Igor Skrjanc, Saso Blazic, Osvaldo E. Agamennoni
ANTSW
2008
Springer
15 years 1 months ago
Modeling Phase Transition in Self-organized Mobile Robot Flocks
We implement a self-organized flocking behavior in a group of mobile robots and analyze its transition from an aligned state to an unaligned state. We briefly describe the robot an...
Ali Emre Turgut, Cristián Huepe, Hande &Cce...