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» Dynamic and Static Influence Models on Starbucks Networks
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114
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BC
2002
193views more  BC 2002»
14 years 9 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
63
Voted
IADIS
2003
14 years 11 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
14 years 9 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 1 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
92
Voted
BMCBI
2006
127views more  BMCBI 2006»
14 years 9 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