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1
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects
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A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects

Li, Zewen ; Liu, Fan ; Yang, Wenjie ; Peng, Shouheng ; Zhou, Jun

IEEE transaction on neural networks and learning systems, 2022-12, Vol.33 (12), p.6999-7019

United States: IEEE

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2
Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective
Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective
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Distributed Recurrent Neural Networks for Cooperative Control of Manipulators: A Game-Theoretic Perspective

Shuai Li ; Jinbo He ; Yangming Li ; Rafique, Muhammad Usman

IEEE transaction on neural networks and learning systems, 2017-02, Vol.28 (2), p.415-426

United States: IEEE

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3
A New Teaching Method of Computer Networks Keeping Pace with the Times-Comment on "Computer Networks: A Top-Down Approach"
A New Teaching Method of Computer Networks Keeping Pace with the Times-Comment on "Computer Networks: A Top-Down Approach"
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A New Teaching Method of Computer Networks Keeping Pace with the Times-Comment on "Computer Networks: A Top-Down Approach"

Du, Hong

Zhongguo Keji Lunwen = China Sciencepaper, 2019-01 (10), p.1173 [Periódico revisado por pares]

Beijing: Jiaoyubu Keji Fazhan Zhongxin

Sem texto completo

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4
The Application and Development of Computer Information Technology in Fashion Design-Comment on "Computer Network Technology Foundation"
The Application and Development of Computer Information Technology in Fashion Design-Comment on "Computer Network Technology Foundation"
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The Application and Development of Computer Information Technology in Fashion Design-Comment on "Computer Network Technology Foundation"

Feng, Yuefang

Zhongguo Keji Lunwen = China Sciencepaper, 2019-01 (7), p.823 [Periódico revisado por pares]

Beijing: Jiaoyubu Keji Fazhan Zhongxin

Sem texto completo

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5
Neural Network-Based Adaptive Dynamic Surface Control for Permanent Magnet Synchronous Motors
Neural Network-Based Adaptive Dynamic Surface Control for Permanent Magnet Synchronous Motors
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Neural Network-Based Adaptive Dynamic Surface Control for Permanent Magnet Synchronous Motors

Yu, Jinpeng ; Shi, Peng ; Dong, Wenjie ; Chen, Bing ; Lin, Chong

IEEE transaction on neural networks and learning systems, 2015-03, Vol.26 (3), p.640-645

United States: IEEE

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6
Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network
Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network
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Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network

Liu, Yu-Ting ; Lin, Yang-Yin ; Wu, Shang-Lin ; Chuang, Chun-Hsiang ; Lin, Chin-Teng

IEEE transaction on neural networks and learning systems, 2016-02, Vol.27 (2), p.347-360

United States: IEEE

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7
Neural Network-Based Motion Control of an Underactuated Wheeled Inverted Pendulum Model
Neural Network-Based Motion Control of an Underactuated Wheeled Inverted Pendulum Model
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Neural Network-Based Motion Control of an Underactuated Wheeled Inverted Pendulum Model

Yang, Chenguang ; Li, Zhijun ; Cui, Rongxin ; Xu, Bugong

IEEE transaction on neural networks and learning systems, 2014-11, Vol.25 (11), p.2004-2016

United States: IEEE

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8
Prediction of data flow in computer network based on linear multi-scale model
Prediction of data flow in computer network based on linear multi-scale model
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Prediction of data flow in computer network based on linear multi-scale model

Duan, Hua-qiong ; Tang, Bin-hui

Shenyang gong ye da xue xue bao, 2017-05 (3)

Shenyang: Shenyang University of Technology

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9
Chaotic Time Series Prediction Based on a Novel Robust Echo State Network
Chaotic Time Series Prediction Based on a Novel Robust Echo State Network
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Chaotic Time Series Prediction Based on a Novel Robust Echo State Network

Li, Decai ; Han, Min ; Wang, Jun

IEEE transaction on neural networks and learning systems, 2012-05, Vol.23 (5), p.787-799

New York, NY: IEEE

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10
SCScore: Synthetic Complexity Learned from a Reaction Corpus
SCScore: Synthetic Complexity Learned from a Reaction Corpus
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SCScore: Synthetic Complexity Learned from a Reaction Corpus

Coley, Connor W ; Rogers, Luke ; Green, William H ; Jensen, Klavs F

Journal of chemical information and modeling, 2018-02, Vol.58 (2), p.252-261 [Periódico revisado por pares]

United States: American Chemical Society

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