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» The Value of Observation for Monitoring Dynamic Systems
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NIPS
1998
13 years 9 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»
13 years 8 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»
13 years 8 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»
13 years 8 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
13 years 10 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...