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» Dynamic and Static Influence Models on Starbucks Networks
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BC
2002
193views more  BC 2002»
15 years 1 months ago
Resonant spatiotemporal learning in large random recurrent networks
Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives...
Emmanuel Daucé, Mathias Quoy, Bernard Doyon
80
Voted
IADIS
2003
15 years 3 months ago
Communication Profiles and Active Attributes
To realize personalized web services and to design adaptable systems it is necessary to have a possibility for modeling the user’s environment and preferences. A common approach...
Peter Dornbusch, Michael Fahrmair, Eiman Mohyeldin...
GIS
2002
ACM
15 years 1 months ago
Calibration of stochastic cellular automata: the application to rural-urban land conversions
Despite the recognition of cellular automata (CA) as a exible and powerful tool for urban growth simulation, the calibration of CA had been largely heuristic until recent eVorts to...
Fulong Wu
ICDCS
1991
IEEE
15 years 5 months ago
Supporting the development of network programs
of ‘‘network computers’’ is inherently lessAbstract predictable than that of more traditional distributed memory systems, such as hypercubes [22], since both theFor computa...
Bernd Bruegge, Peter Steenkiste
BMCBI
2006
127views more  BMCBI 2006»
15 years 1 months ago
On the attenuation and amplification of molecular noise in genetic regulatory networks
Background: Noise has many important roles in cellular genetic regulatory functions at the nanomolar scale. At present, no good theory exists for identifying all possible mechanis...
Bor-Sen Chen, Yu-Chao Wang