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NIPS
1998
14 years 11 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis
HYBRID
2007
Springer
15 years 3 months ago
Groupoids in Control Systems and the Reachability Problem for a Class of Quantized Control Systems with Nonabelian Symmetries
The aim of this paper is twofold. On one hand we present an approach to the general problem of nonlinear control in the framework of (differentiable) groupoids, which, in our opin...
Alessandro Arsie, Emilio Frazzoli
93
Voted
EAAI
2007
199views more  EAAI 2007»
14 years 9 months ago
Nonlinear system modeling and robust predictive control based on RBF-ARX model
An integrated modeling and robust model predictive control (MPC) approach is proposed for a class of nonlinear systems with unknown steady state. First, the nonlinear system is id...
Hui Peng, Zi-Jiang Yang, Weihua Gui, Min Wu, Hideo...
CDC
2010
IEEE
101views Control Systems» more  CDC 2010»
14 years 4 months ago
Identification of mixed linear/nonlinear state-space models
The primary contribution of this paper is an algorithm capable of identifying parameters in certain mixed linear/nonlinear state-space models, containing conditionally linear Gauss...
Fredrik Lindsten, Thomas B. Schön
ICML
2006
IEEE
15 years 10 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh