Neural Networks, Volume 141

Volume 141, September 2021

Learning Systems

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  Hao Zhang, DeLiang Wang:
  Deep ANC: A deep learning approach to active noise control. 1-10
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  Yingqiu Zhu, Danyang Huang, Yuan Gao, Rui Wu, Yu Chen, Bo Zhang, Hansheng Wang:
  Automatic, dynamic, and nearly optimal learning rate specification via local quadratic approximation. 11-29
• 
  Joel Zirkle, Leonid L. Rubchinsky:
  Noise effect on the temporal patterns of neural synchrony. 30-39

Mathematical and Computational Analysis

• 
  Hailing Dong, Ming Luo, Mingqing Xiao:
  Synchronization for stochastic coupled networks with Lévy noise via event-triggered control. 40-51

Learning Systems

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  Ziping Zhao, Qifei Li, Zixing Zhang, Nicholas Cummins, Haishuai Wang, Jianhua Tao, Björn W. Schuller:
  Combining a parallel 2D CNN with a self-attention Dilated Residual Network for CTC-based discrete speech emotion recognition. 52-60
• 
  Yalan Ye, Ziwei Huang, Tongjie Pan, Jingjing Li, Heng Tao Shen:
  Reducing bias to source samples for unsupervised domain adaptation. 61-71
• 
  Lin Li, Zheng Li, Yan Liu, Qingyang Hong:
  Deep joint learning for language recognition. 72-86
• 
  Cian Ryan, Brian O'Sullivan, Amr Elrasad, Aisling Cahill, Joe Lemley, Paul Kielty, Christoph Posch, Etienne Perot:
  Real-time face & eye tracking and blink detection using event cameras. 87-97

Neuroscience

• 
  Jiejie Chen, Boshan Chen, Zhigang Zeng:
  Exponential quasi-synchronization of coupled delayed memristive neural networks via intermittent event-triggered control. 98-106

Mathematical and Computational Analysis

• 
  Zhenyuan Guo, Jingxuan Ci, Jun Wang:
  Multi-periodicity of switched neural networks with time delays and periodic external inputs under stochastic disturbances. 107-119

Engineering and Applications

• 
  Priyadarshini Panda, Kaushik Roy:
  Implicit adversarial data augmentation and robustness with Noise-based Learning. 120-132
• 
  Daoguang Yang, Hamid Reza Karimi, Kangkang Sun:
  Residual wide-kernel deep convolutional auto-encoder for intelligent rotating machinery fault diagnosis with limited samples. 133-144

Learning Systems

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  Ryan Burt, Nina N. Thigpen, Andreas Keil, José C. Príncipe:
  Unsupervised foveal vision neural architecture with top-down attention. 145-159

Mathematical and Computational Analysis

• 
  Zuowei Shen, Haizhao Yang, Shijun Zhang:
  Neural network approximation: Three hidden layers are enough. 160-173
• 
  Baojun Miao, Xuechen Li, Jungang Lou, Jianquan Lu:
  Pinning bipartite synchronization for coupled reaction-diffusion neural networks with antagonistic interactions and switching topologies. 174-183

Learning Systems

• 
  Frédéric Allaire, Vivien Mallet, Jean-Baptiste Filippi:
  Emulation of wildland fire spread simulation using deep learning. 184-198

Neuroscience

• 
  Yihong Wang, Xuying Xu, Rubin Wang:
  Modeling the grid cell activity on non-horizontal surfaces based on oscillatory interference modulated by gravity. 199-210

Learning Systems

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  Venkata Srikanth Nallanthighal, Zohreh Mostaani, Aki Härmä, Helmer Strik, Mathew Magimai-Doss:
  Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings. 211-224
• 
  Guanjun Li, Shan Liang, Shuai Nie, Wenju Liu, Zhanlei Yang:
  Deep neural network-based generalized sidelobe canceller for dual-channel far-field speech recognition. 225-237

Engineering and Applications

• 
  Hangting Chen, Pengyuan Zhang:
  A dual-stream deep attractor network with multi-domain learning for speech dereverberation and separation. 238-248

Learning Systems

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  Yanping Chen, Weizhe Yang, Kai Wang, Yongbin Qin, Ruizhang Huang, Qinghua Zheng:
  A neuralized feature engineering method for entity relation extraction. 249-260

Mathematical and Computational Analysis

• 
  Shuchen Wu, Xiaodi Li, Yanhui Ding:
  Saturated impulsive control for synchronization of coupled delayed neural networks. 261-269
• 
  Rongzhen Zhao, Zhenzhi Wu, Qikun Zhang:
  Learnable Heterogeneous Convolution: Learning both topology and strength. 270-280
• 
  Qiang Li, Jinling Liang, Hong Qu:
  H∞ estimation for stochastic semi-Markovian switching CVNNs with missing measurements and mode-dependent delays. 281-293

Learning Systems

• 
  Gabriel Turinici:
  Radon-Sobolev Variational Auto-Encoders. 294-305
• 
  Rui Liu, Berrak Sisman, Yixing Lin, Haizhou Li:
  FastTalker: A neural text-to-speech architecture with shallow and group autoregression. 306-314
• 
  Sara Dahmani, Vincent Colotte, Valérian Girard, Slim Ouni:
  Learning emotions latent representation with CVAE for text-driven expressive audiovisual speech synthesis. 315-329

Mathematical and Computational Analysis

• 
  Matthew Farrell, Stefano Recanatesi, R. Clay Reid, Stefan Mihalas, Eric Shea-Brown:
  Autoencoder networks extract latent variables and encode these variables in their connectomes. 330-343

Learning Systems

• 
  Chengdai Huang, Juan Wang, Xiaoping Chen, Jinde Cao:
  Bifurcations in a fractional-order BAM neural network with four different delays. 344-354

Engineering and Applications

• 
  Ziqiang Zheng, Zhibin Yu, Yang Wu, Haiyong Zheng, Bing Zheng, Minho Lee:
  Generative Adversarial Network with Multi-branch Discriminator for imbalanced cross-species image-to-image translation. 355-371

Learning Systems

• 
  Guangzhi Sun, Chao Zhang, Philip C. Woodland:
  Combination of deep speaker embeddings for diarisation. 372-384

Engineering and Applications

• 
  Wenchao Gu, Zongjie Li, Cuiyun Gao, Chaozheng Wang, Hongyu Zhang, Zenglin Xu, Michael R. Lyu:
  CRaDLe: Deep code retrieval based on semantic Dependency Learning. 385-394

Learning Systems

• 
  Yufeng Wang, Dan Li, Xiang Li, Min Yang:
  PC-GAIN: Pseudo-label conditional generative adversarial imputation networks for incomplete data. 395-403

Mathematical and Computational Analysis

• 
  Alexander Cloninger, Timo Klock:
  A deep network construction that adapts to intrinsic dimensionality beyond the domain. 404-419

Learning Systems

• 
  Donghyun Lee, Dingheng Wang, Yukuan Yang, Lei Deng, Guangshe Zhao, Guoqi Li:
  QTTNet: Quantized tensor train neural networks for 3D object and video recognition. 420-432

Neuroscience

• 
  Ali Al-Saegh, Shefa A. Dawwd, Jassim M. Abdul-Jabbar:
  CutCat: An augmentation method for EEG classification. 433-443