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    CMSB
    2008
    Springer
    168views Applied Computing» more  CMSB 2008»
    Automatic Complexity Analysis and Model Reduction of Nonlinear Biochemical Systems
    13 years 9 months ago
    Automatic Complexity Analysis and Model Reduction of Nonlinear Biochemical Systems
    Download  omnibus.uni-freiburg.de
    Kinetic models for biochemical systems often comprise a large amount of coupled differential equations with species concentrations varying on different time scales. In this paper w...
    Dirk Lebiedz, Dominik Skanda, Marc Fein
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    DAC
    2003
    ACM
    132views Computer Architecture» more  DAC 2003»
    A TBR-based trajectory piecewise-linear algorithm for generating accurate low-order models for nonlinear analog circuits and MEM
    14 years 8 months ago
    A TBR-based trajectory piecewise-linear algorithm for generating accurate low-order models for nonlinear analog circuits and MEM
    Download  www.mit.edu
    In this paper we propose a method for generating reduced models for a class of nonlinear dynamical systems, based on truncated balanced realization (TBR) algorithm and a recently ...
    Dmitry Vasilyev, Michal Rewienski, Jacob White
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    APPINF
    2003
    358views Information Technology» more  APPINF 2003»
    Preventing Computational Chaos in Asynchronous Neural Networks
    13 years 8 months ago
    Preventing Computational Chaos in Asynchronous Neural Networks
    Download  www.ornl.gov
    One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
    Jacob Barhen, Vladimir Protopopescu
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    AAAI
    2006
    165views Intelligent Agents» more  AAAI 2006»
    Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
    13 years 8 months ago
    Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
    Download  www.aaai.org
    The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
    David Wingate, Satinder P. Singh
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    ICML
    2006
    IEEE
    180views Machine Learning» more  ICML 2006»
    Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
    14 years 8 months ago
    Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
    Download  www.eecs.umich.edu
    The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
    David Wingate, Satinder P. Singh
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