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» Approximate Learning of Dynamic Models
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TSP
2010
14 years 8 months ago
Double sparsity: learning sparse dictionaries for sparse signal approximation
Abstract--An efficient and flexible dictionary structure is proposed for sparse and redundant signal representation. The proposed sparse dictionary is based on a sparsity model of ...
Ron Rubinstein, Michael Zibulevsky, Michael Elad
IJBC
2002
109views more  IJBC 2002»
15 years 1 months ago
Cnn Dynamics represents a Broader Class than PDES
The relationship between Cellular Nonlinear Networks (CNNs) and Partial Differential Equations (PDEs) is investigated. The equivalence between discrete-space CNN models and contin...
Marco Gilli, Tamás Roska, Leon O. Chua, Pie...
NIPS
2003
15 years 3 months ago
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System
We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are...
Marc Toussaint
NECO
2002
104views more  NECO 2002»
15 years 1 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen
AMS
2007
Springer
296views Robotics» more  AMS 2007»
15 years 8 months ago
Learning the Inverse Model of the Dynamics of a Robot Leg by Auto-imitation
Abstract Walking, running and hopping are based on self-stabilizing oscillatory activity. In contrast, aiming movements serve to direct a limb to a desired location and demand a qu...
Karl-Theodor Kalveram, André Seyfarth