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    ESANN
    2004
    115views Neural Networks» more  ESANN 2004»
    Input arrival-time-dependent decoding scheme for a spiking neural network
    13 years 9 months ago
    Input arrival-time-dependent decoding scheme for a spiking neural network
    Download  www.dice.ucl.ac.be
    Spiking neurons model a type of biological neural system where information is encoded with spike times. In this paper, a new method for decoding input spikes according to their abs...
    Hesham H. Amin, Robert H. Fujii
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    EAAI
    2006
    123views more  EAAI 2006»
    Imitation learning with spiking neural networks and real-world devices
    13 years 7 months ago
    Imitation learning with spiking neural networks and real-world devices
    Download  www.igi.tugraz.at
    This article is about a new approach in robotic learning systems. It provides a method to use a real-world device that operates in real-time, controlled through a simulated recurr...
    Harald Burgsteiner
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    ICASSP
    2007
    IEEE
    133views Signal Processing» more  ICASSP 2007»
    Fundamental Detection and Estimation Limits in Spike Sorting
    14 years 1 months ago
    Fundamental Detection and Estimation Limits in Spike Sorting
    Download  www.ece.rice.edu
    Spike sorting refers to the detection and classification of electric potentials (spikes) from multi-neuron recordings, a difficult but essential pre-processing step before neura...
    Mona A. Sheikh, Don H. Johnson
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    ICANN
    2009
    Springer
    145views Neural Networks» more  ICANN 2009»
    Learning from Examples to Generalize over Pose and Illumination
    14 years 3 days ago
    Learning from Examples to Generalize over Pose and Illumination
    Download  ftp.neuroinformatik.rub.de
    We present a neural system that recognizes faces under strong variations in pose and illumination. The generalization is learnt completely on the basis of examples of a subset of p...
    Marco K. Müller, Rolf P. Würtz
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    NIPS
    2003
    139views Information Technology» more  NIPS 2003»
    Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
    13 years 8 months ago
    Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
    Download  pillowlab.cps.utexas.edu
    Recent work has examined the estimation of models of stimulus-driven neural activity in which some linear filtering process is followed by a nonlinear, probabilistic spiking stag...
    Jonathan Pillow, Liam Paninski, Eero P. Simoncelli
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