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» Modeling Sensorimotor Learning with Linear Dynamical Systems
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AAAI
2006
13 years 9 months ago
Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
David Wingate, Satinder P. Singh
ASC
2007
13 years 7 months ago
An approximate stability analysis of nonlinear systems described by Universal Learning Networks
Stability is one of the most important subjects in control systems. As for the stability of nonlinear dynamical systems, Lyapunov’s direct method and linearized stability analys...
Kotaro Hirasawa, Shingo Mabu, Shinji Eto, Jinglu H...
BMCBI
2007
173views more  BMCBI 2007»
13 years 7 months ago
Predicting state transitions in the transcriptome and metabolome using a linear dynamical system model
Background: Modelling of time series data should not be an approximation of input data profiles, but rather be able to detect and evaluate dynamical changes in the time series dat...
Ryoko Morioka, Shigehiko Kanaya, Masami Y. Hirai, ...
MMAS
2011
Springer
13 years 2 months ago
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
Phaedon-Stelios Koutsourelakis, Elias Bilionis
DAGSTUHL
2009
13 years 8 months ago
Statistical Mechanics of On-line Learning
We introduce and discuss the application of statistical physics concepts in the context of on-line machine learning processes. The consideration of typical properties of very large...
Michael Biehl, Nestor Caticha, Peter Riegler