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IPSN
2003
Springer
14 years 2 months ago
Maximum Mutual Information Principle for Dynamic Sensor Query Problems
In this paper we study a dynamic sensor selection method for Bayesian filtering problems. In particular we consider the distributed Bayesian Filtering strategy given in [1] and sh...
Emre Ertin, John W. Fisher, Lee C. Potter
ICAI
2007
13 years 11 months ago
Dynamic Programming Algorithm for Training Functional Networks
Abstract— The paper proposes a dynamic programming algorithm for training of functional networks. The algorithm considers each node as a state. The problem is formulated as find...
Emad A. El-Sebakhy, Salahadin Mohammed, Moustafa E...
BLISS
2009
IEEE
13 years 10 months ago
Recognition of Dynamic Texture Patterns Using CHLAC Features
In this paper, we propose a statistical scheme for recognizing three-dimensional textures shown in motion images, which we call dynamic textures. The texture characteristics emerg...
Takumi Kobayashi, Tetsuya Higuchi, Tsuneharu Miyaj...
AROBOTS
2008
104views more  AROBOTS 2008»
13 years 9 months ago
Modeling dynamic scenarios for local sensor-based motion planning
This paper addresses the modeling of the static and dynamic parts of the scenario and how to use this information with a sensor-based motion planning system. The contribution in th...
Luis Montesano, Javier Minguez, Luis Montano
NECO
2002
104views more  NECO 2002»
13 years 9 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