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    JSCIC
    2008
    107views more  JSCIC 2008»
    A Hierarchy of Approximations of the Master Equation Scaled by a Size Parameter
    14 years 9 months ago
    A Hierarchy of Approximations of the Master Equation Scaled by a Size Parameter
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    Solutions of the master equation are approximated using a hierarchy of models based on the solution of ordinary differential equations: the macroscopic equations, the linear noise...
    Lars Ferm, Per Lötstedt, Andreas Hellander
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    ENTCS
    2007
    92views more  ENTCS 2007»
    The MoR-Trust Distributed Trust Management System: Design and Simulation Results
    14 years 9 months ago
    The MoR-Trust Distributed Trust Management System: Design and Simulation Results
    Download  www.dmst.aueb.gr
    MoR-Trust is a purely decentralized peer-to-peer trust management system, targeted towards networks and applications supporting transactions or collaborations of a quantitative na...
    Stephanos Androutsellis-Theotokis, Diomidis Spinel...
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    MONET
    2006
    170views more  MONET 2006»
    Decentralized Utility-based Sensor Network Design
    14 years 9 months ago
    Decentralized Utility-based Sensor Network Design
    Download  ceng.usc.edu
    Wireless sensor networks consist of energy-constrained sensor nodes operating unattended in highly dynamic environments. In this paper, we advocate a systematic decentralized appro...
    Narayanan Sadagopan, Mitali Singh, Bhaskar Krishna...
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    SIAMSC
    2008
    133views more  SIAMSC 2008»
    Numerical Variational Methods Applied to Cylinder Buckling
    14 years 9 months ago
    Numerical Variational Methods Applied to Cylinder Buckling
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    We review and compare different computational variational methods applied to a system of fourth order equations that arises as a model of cylinder buckling. We describe both the di...
    Jirí Horák, Gabriel J. Lord, Mark A....
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    TNN
    2008
    82views more  TNN 2008»
    Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
    14 years 9 months ago
    Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks
    Download  www.ge.ieiit.cnr.it
    In this paper, a general method for the numerical solution of maximum-likelihood estimation (MLE) problems is presented; it adopts the deterministic learning (DL) approach to find ...
    Cristiano Cervellera, Danilo Macciò, Marco ...
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