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    IJCAI
    2007
    161views Artificial Intelligence» more  IJCAI 2007»
    Extracting Propositional Rules from Feed-forward Neural Networks - A New Decompositional Approach
    13 years 9 months ago
    Extracting Propositional Rules from Feed-forward Neural Networks - A New Decompositional Approach
    Download  sunsite.informatik.rwth-aachen.de
    In this paper, we present a new decompositional approach for the extraction of propositional rules from feed-forward neural networks of binary threshold units. After decomposing t...
    Sebastian Bader, Steffen Hölldobler, Valentin...
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    ERSA
    2006
    91views Hardware» more  ERSA 2006»
    Intrinsic Embedded Hardware Evolution of Block-based Neural Networks
    13 years 9 months ago
    Intrinsic Embedded Hardware Evolution of Block-based Neural Networks
    Download  ww1.ucmss.com
    - An intrinsic embedded online evolution system has been designed using Block-based neural networks and implemented on Xilinx VirtexIIPro FPGAs. The designed network can dynamicall...
    Saumil Merchant, Gregory D. Peterson, Seong Kong
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    ESANN
    1998
    96views Neural Networks» more  ESANN 1998»
    A self-organising neural network for modelling cortical development
    13 years 9 months ago
    A self-organising neural network for modelling cortical development
    Download  www.dice.ucl.ac.be
    This paper presents a novel self-organising neural network. It has been developed for use as a simpli ed model of cortical development. Unlike many other models of topological map...
    Michael W. Spratling, Gillian Hayes
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    NIPS
    1998
    85views Information Technology» more  NIPS 1998»
    Global Optimisation of Neural Network Models via Sequential Sampling
    13 years 9 months ago
    Global Optimisation of Neural Network Models via Sequential Sampling
    Download  mi.eng.cam.ac.uk
    We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
    João F. G. de Freitas, Mahesan Niranjan, Ar...
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    HAIS
    2008
    Springer
    99views Artificial Intelligence» more  HAIS 2008»
    An Evolutionary Approach for Tuning Artificial Neural Network Parameters
    13 years 9 months ago
    An Evolutionary Approach for Tuning Artificial Neural Network Parameters
    Download  www.cin.ufpe.br
    The widespread use of artificial neural networks and the difficult work regarding the correct specification (tuning) of parameters for a given problem are the main aspects that mot...
    Leandro M. Almeida, Teresa Bernarda Ludermir
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