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sylvain_chevallier neural [21 articles]

最近 sylvain_chevallier さんのライブラリに追加された論文の中から タグ neural. You can also see everyone's neural.
  • Visualization of neural networks using saliency maps
    Neural Networks, 1995. Proceedings., IEEE International Conference on, Vol. 4 (1995), pp. 2085-2090 vol.4.
    by NJS Morch, U Kjems, LK Hansen, C Svarer, I Law, B Lautrup, S Strother, K Rehm
    posted to visualization saliency neural networks by sylvain_chevallier on 2008-08-15 19:07:28 as read
  • A neural network implementation of a saliency map model.
    Neural Netw (8 May 2006)
    by Matthew de Brecht, Jun Saiki
  • A Distributed Computational Model of Spatial Memory Anticipation During a Visual Search Task
    Anticipatory Behavior in Adaptive Learning Systems (2007), pp. 170-188.
    by Jérémy Fix, Julien Vitay, Nicolas Rougier
    posted to vision system robotics neural field attention by sylvain_chevallier on 2008-08-14 15:54:38 as **
  • A Distributed Model of Spatial Visual Attention
    Biomimetic Neural Learning for Intelligent Robots (2005), pp. 54-72.
    by Julien Vitay, Nicolas P Rougier, Frédéric Alexandre
  • Synaptic plasticity: taming the beast.
    Nat Neurosci, Vol. 3 Suppl (November 2000), pp. 1178-1183.
    by LF Abbott, SB Nelson
  • Distinguishing theoretical synaptic potentials computed for different soma-dendritic distributions of synaptic input.
    J Neurophysiol, Vol. 30, No. 5. (September 1967), pp. 1138-1168.
    by W Rall
  • An efficient method for computing synaptic conductances based on a kinetic model of receptor binding
    Neural Comput., Vol. 6, No. 1. (January 1994), pp. 14-18.
  • Which model to use for cortical spiking neurons?
    Neural Networks, IEEE Transactions on, Vol. 15, No. 5. (2004), pp. 1063-1070.
  • Analytical integrate-and-fire neuron models with conductance-based dynamics for event-driven simulation strategies.
    Neural Comput, Vol. 18, No. 9. (September 2006), pp. 2146-2210.
  • Conductance-based integrate-and-fire models
    Neural Comput., Vol. 9, No. 3. (April 1997), pp. 503-514.
    by Alain Destexhe
  • Lapicque's introduction of the integrate-and-fire model neuron (1907)
    Brain Research Bulletin, Vol. 50, No. 5-6. ( 1999), pp. 303-304.
    by LF Abbott
  • A quantitative description of membrane current and its application to conduction and excitation in nerve
    Bulletin of Mathematical Biology, Vol. 52, No. 1. (January 1990), pp. 25-71.
    by A Hodgkin, A Huxley
  • Energy-Efficient Coding with Discrete Stochastic Events
    Neural Comp., Vol. 14, No. 6. (1 June 2002), pp. 1323-1346.
    by Susanne Schreiber, Christian K Machens, Andreas V Herz, Simon B Laughlin
    posted to theory temporal neural events energy coding by sylvain_chevallier on 2008-06-27 17:20:54 as read
  • Type I membranes, phase resetting curves, and synchrony
    Neural Comput., Vol. 8, No. 5. (July 1996), pp. 979-1001.
    by Bard Ermentrout
  • Parabolic Bursting in an Excitable System Coupled with a Slow Oscillation
    SIAM Journal on Applied Mathematics, Vol. 46, No. 2. (1986), pp. 233-253.
  • Neurons with graded response have collective computational properties like those of two-state neurons.
    Proc Natl Acad Sci U S A, Vol. 81, No. 10. (May 1984), pp. 3088-3092.
    by JJ Hopfield
  • The Handbook of Brain Theory and Neural Networks (Bradford Book)
    (31 July 1998)
    posted to theory reference neural network learning book artificial by sylvain_chevallier on 2008-06-24 16:05:08 as read
  • A logical calculus of the ideas immanent in nervous activity
    Bulletin of Mathematical Biology, Vol. 5, No. 4. (21 December 1943), pp. 115-133.
    by Warren Mcculloch, Walter Pitts
  • Internal models for visual perception
    Biological Cybernetics, Vol. V88, No. 5. (1 May 2003), pp. 409-417.
    by Wolfram Erlhagen
  • Transition Cells and Neural Fields for Navigation and Planning
    Mechanisms, Symbols, and Models Underlying Cognition (2005), pp. 346-355.
    by Nicolas Cuperlier, Mathias Quoy, Philippe Laroque, Philippe Gaussier
  • Sequence learning using the neural coding
    Computational Methods in Neural Modeling (2003), pp. 1036-1037.
    by Sorin Moga, Philippe Gaussier, Jean-Paul Banquet
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