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» Combining Simple Models to Approximate Complex Dynamics
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INFOCOM
2010
IEEE
13 years 6 months ago
Routing for Energy Minimization in the Speed Scaling Model
Abstract—We study network optimization that considers energy minimization as an objective. Studies have shown that mechanisms such as speed scaling can significantly reduce the ...
Matthew Andrews, Antonio Fernández, Lisa Zh...
CIBCB
2006
IEEE
14 years 1 months ago
A Stochastic model to estimate the time taken for Protein-Ligand Docking
Abstract— Quantum mechanics and molecular dynamic simulation provide important insights into structural configurations and molecular interaction data today. To extend this atomi...
Preetam Ghosh, Samik Ghosh, Kalyan Basu, Sajal K. ...
SBRN
2000
IEEE
14 years 3 days ago
Non-Linear Modelling and Chaotic Neural Networks
This paper proposes a simple methodology to construct an iterative neural network which mimics a given chaotic time series. The methodology uses the Gamma test to identify a suita...
Antonia J. Jones, Steve Margetts, Peter Durrant, A...
ECAI
2006
Springer
13 years 11 months ago
Polynomial Conditional Random Fields for Signal Processing
We describe Polynomial Conditional Random Fields for signal processing tasks. It is a hybrid model that combines the ability of Polynomial Hidden Markov models for modeling complex...
Trinh Minh Tri Do, Thierry Artières
IROS
2007
IEEE
152views Robotics» more  IROS 2007»
14 years 2 months ago
Integral control of humanoid balance
— This paper presents a balance controller that allows a humanoid to recover from large disturbances and still maintain an upright posture. Balance is achieved by integral contro...
Benjamin Stephens