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    IJCNN
    2007
    IEEE
    118views Neural Networks» more  IJCNN 2007»
    System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
    14 years 3 months ago
    System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
    Download  www.cs.utexas.edu
    — A single biological neuron is able to perform complex computations that are highly nonlinear in nature, adaptive, and superior to the perceptron model. A neuron is essentially ...
    Manish Saggar, Tekin Meriçli, Sari Andoni, ...
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    ASC
    2007
    153views Artificial Intelligence» more  ASC 2007»
    Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems
    13 years 9 months ago
    Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems
    Download  icsl.gatech.edu
    We present the results of our investigation into the use of Genetic Algorithms (GAs) for identifying near optimal design parameters of diagnostic systems that are based on Artifici...
    Abhinav Saxena, Ashraf Saad
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    TNN
    2008
    138views more  TNN 2008»
    A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
    13 years 8 months ago
    A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent
    Download  www.ece.utk.edu
    This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
    Zhenzhen Liu, Itamar Elhanany
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    ESWA
    2010
    118views more  ESWA 2010»
    Integrating independent component analysis-based denoising scheme with neural network for stock price prediction
    13 years 7 months ago
    Integrating independent component analysis-based denoising scheme with neural network for stock price prediction
    Download  w3.cyu.edu.tw
    The forecasting of stock price is one of the most challenging tasks in investment/financial decision-making since stock prices/indices are inherently noisy and non-stationary. In ...
    Chi-Jie Lu
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    TIT
    1998
    79views more  TIT 1998»
    Capacity of Two-Layer Feedforward Neural Networks with Binary Weights
    13 years 8 months ago
    Capacity of Two-Layer Feedforward Neural Networks with Binary Weights
    Download  users.ece.gatech.edu
    — The lower and upper bounds for the information capacity of two-layer feedforward neural networks with binary interconnections, integer thresholds for the hidden units, and zero...
    Chuanyi Ji, Demetri Psaltis
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