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Refinado por: assunto: Cognitive Neuroscience remover
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1
Connectionist models of neurons, learning processes, and artificial intelligence 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, Granada, Spain, June 13-15, 2001 : proceedings. Pt. I
Connectionist models of neurons, learning processes, and artificial intelligence 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, Granada, Spain, June 13-15, 2001 : proceedings. Pt. I
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Connectionist models of neurons, learning processes, and artificial intelligence 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, Granada, Spain, June 13-15, 2001 : proceedings. Pt. I

International Work-Conference on Artificial and Natural Neural Networks (6th 2001 Granada, Spain) J Mira (José); A Prieto (Alberto)

Berlin Springer London c2001

Localização: ICMC - Inst. Ciên. Mat. Computação    (68-02 LNCS v.2084 ) e outros locais(Acessar)

2
Computational and ambient intelligence 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastian, Spain, June 20-22, 2007 : proceedings
Computational and ambient intelligence 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastian, Spain, June 20-22, 2007 : proceedings
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Computational and ambient intelligence 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastian, Spain, June 20-22, 2007 : proceedings

International Work-Conference on Artificial and Natural Neural Networks (9th 2007 San Sebasti an, Spain) Alberto Prieto; Joan Cabestany; Manuel Graña; Francisco Sandoval

Berlin Springer New York c2007

Localização: IME - Inst. Matemática e Estatística    (S L471c v.4507 )(Acessar)

3
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
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NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data

Kasabov, Nikola K.

Neural networks, 2014-04, Vol.52, p.62-76 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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4
Global asymptotic stability analysis for delayed neural networks using a matrix-based quadratic convex approach
Global asymptotic stability analysis for delayed neural networks using a matrix-based quadratic convex approach
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Global asymptotic stability analysis for delayed neural networks using a matrix-based quadratic convex approach

Zhang, Xian-Ming ; Han, Qing-Long

Neural networks, 2014-06, Vol.54, p.57-69 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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5
Stochastic sampled-data control for state estimation of time-varying delayed neural networks
Stochastic sampled-data control for state estimation of time-varying delayed neural networks
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Stochastic sampled-data control for state estimation of time-varying delayed neural networks

Lee, Tae H. ; Park, Ju H. ; Kwon, O.M. ; Lee, S.M.

Neural networks, 2013-10, Vol.46, p.99-108 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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6
Evolving RBF neural networks for rainfall prediction using hybrid particle swarm optimization and genetic algorithm
Evolving RBF neural networks for rainfall prediction using hybrid particle swarm optimization and genetic algorithm
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Evolving RBF neural networks for rainfall prediction using hybrid particle swarm optimization and genetic algorithm

Wu, Jiansheng ; Long, Jin ; Liu, Mingzhe

Neurocomputing (Amsterdam), 2015-01, Vol.148, p.136-142 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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7
Review and performance comparison of SVM- and ELM-based classifiers
Review and performance comparison of SVM- and ELM-based classifiers
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Review and performance comparison of SVM- and ELM-based classifiers

Chorowski, Jan ; Wang, Jian ; Zurada, Jacek M.

Neurocomputing (Amsterdam), 2014-03, Vol.128, p.507-516 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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8
An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks
An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks
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An adaptive filtering approach for electrocardiogram (ECG) signal noise reduction using neural networks

Poungponsri, Suranai ; Yu, Xiao-Hua

Neurocomputing (Amsterdam), 2013-10, Vol.117, p.206-213 [Periódico revisado por pares]

Amsterdam: Elsevier B.V

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9
Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world
Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world
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Adaptive Resonance Theory: How a brain learns to consciously attend, learn, and recognize a changing world

Grossberg, Stephen

Neural networks, 2013-01, Vol.37, p.1-47 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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10
A probabilistic neural network for earthquake magnitude prediction
A probabilistic neural network for earthquake magnitude prediction
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A probabilistic neural network for earthquake magnitude prediction

Adeli, Hojjat ; Panakkat, Ashif

Neural networks, 2009-09, Vol.22 (7), p.1018-1024 [Periódico revisado por pares]

Kidlington: Elsevier Ltd

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