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Back propagation theory, architectures, and applications
Back propagation theory, architectures, and applications
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Back propagation theory, architectures, and applications

Yves Chauvin Ph. D.; David E Rumelhart

Hillsdale, N.J. Lawrence Erlbaum Associates c1995

Localização: ICMC - Inst. Ciên. Mat. Computação    (68T45.01 B126 e.1 )(Acessar)

2
Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism
Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism
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Livro 		Adicionar ao Meu Espaço

Parallel implementations of backpropagation neural networks on transputers a study of training set parallelism

P. Saratchandran N Sundararajan; Shou King Foo

Singapore World Scientific River Edge, NJ c1996

Localização: EPBC - Esc. Politécnica-Bib Central    (004.272 Sa71p )(Acessar)

3
Deep physical neural networks trained with backpropagation
Deep physical neural networks trained with backpropagation
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Artigo 		Adicionar ao Meu Espaço

Deep physical neural networks trained with backpropagation

Wright, Logan G ; Onodera, Tatsuhiro ; Stein, Martin M ; Wang, Tianyu ; Schachter, Darren T ; Hu, Zoey ; McMahon, Peter L

Nature (London), 2022-01, Vol.601 (7894), p.549-555 [Periódico revisado por pares]

England: Nature Publishing Group

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4
Design of Aperture-Multiplexing Metasurfaces via Back-Propagation Neural Network: Independent Control of Orthogonally-Polarized Waves
Design of Aperture-Multiplexing Metasurfaces via Back-Propagation Neural Network: Independent Control of Orthogonally-Polarized Waves
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Artigo 		Adicionar ao Meu Espaço

Design of Aperture-Multiplexing Metasurfaces via Back-Propagation Neural Network: Independent Control of Orthogonally-Polarized Waves

Zhu, Ruichao ; Wang, Jiafu ; Han, Yajuan ; Sui, Sai ; Qiu, Tianshuo ; Jia, Yuxiang ; Feng, Mingde ; Wang, Xiaofeng ; Zheng, Lin ; Qu, Shaobo

IEEE transactions on antennas and propagation, 2022-06, Vol.70 (6), p.1-1 [Periódico revisado por pares]

New York: IEEE

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5
Training Spiking Neural Networks Using Lessons From Deep Learning
Training Spiking Neural Networks Using Lessons From Deep Learning
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Training Spiking Neural Networks Using Lessons From Deep Learning

Eshraghian, Jason K. ; Ward, Max ; Neftci, Emre O. ; Wang, Xinxin ; Lenz, Gregor ; Dwivedi, Girish ; Bennamoun, Mohammed ; Jeong, Doo Seok ; Lu, Wei D.

Proceedings of the IEEE, 2023-09, Vol.111 (9), p.1016-1054 [Periódico revisado por pares]

New York: IEEE

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6
A novel architecture combined with optimal parameters for back propagation neural networks applied to anomaly network intrusion detection
A novel architecture combined with optimal parameters for back propagation neural networks applied to anomaly network intrusion detection
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A novel architecture combined with optimal parameters for back propagation neural networks applied to anomaly network intrusion detection

Chiba, Zouhair ; Abghour, Noureddine ; Moussaid, Khalid ; El Omri, Amina ; Rida, Mohamed

Computers & security, 2018-06, Vol.75, p.36-58 [Periódico revisado por pares]

Amsterdam: Elsevier Ltd

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7
Advancing theoretical understanding and practical performance of signal processing for nonlinear optical communications through machine learning
Advancing theoretical understanding and practical performance of signal processing for nonlinear optical communications through machine learning
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Advancing theoretical understanding and practical performance of signal processing for nonlinear optical communications through machine learning

Fan, Qirui ; Zhou, Gai ; Gui, Tao ; Lu, Chao ; Lau, Alan Pak Tao

Nature communications, 2020-07, Vol.11 (1), p.3694-3694, Article 3694 [Periódico revisado por pares]

London: Nature Publishing Group

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8
Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems
Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems
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Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems

Bai, Bin ; Zhang, Junyi ; Wu, Xuan ; wei Zhu, Guang ; Li, Xinye

Expert systems with applications, 2021-09, Vol.177, p.114952, Article 114952 [Periódico revisado por pares]

New York: Elsevier Ltd

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9
NOx emissions prediction based on mutual information and back propagation neural network using correlation quantitative analysis
NOx emissions prediction based on mutual information and back propagation neural network using correlation quantitative analysis
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NOx emissions prediction based on mutual information and back propagation neural network using correlation quantitative analysis

Wang, Guoyang ; Awad, Omar I. ; Liu, Shiyu ; Shuai, Shijin ; Wang, Zhiming

Energy (Oxford), 2020-05, Vol.198, p.117286, Article 117286 [Periódico revisado por pares]

Oxford: Elsevier Ltd

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10
A solution to the learning dilemma for recurrent networks of spiking neurons
A solution to the learning dilemma for recurrent networks of spiking neurons
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A solution to the learning dilemma for recurrent networks of spiking neurons

Bellec, Guillaume ; Scherr, Franz ; Subramoney, Anand ; Hajek, Elias ; Salaj, Darjan ; Legenstein, Robert ; Maass, Wolfgang

Nature communications, 2020-07, Vol.11 (1), p.3625-3625, Article 3625 [Periódico revisado por pares]

London: Nature Publishing Group

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Deste Autor:

  1. Sundararajan, N
  2. Chauvin, Y
  3. Rumelhart, D
  4. Foo, S
  5. Saratchandran, P

Neste Assunto:

  1. Neural Networks
  2. Science & Technology
  3. Back Propagation
  4. Technology
  5. Back Propagation Networks

  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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