| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A biologically plausible supervised learning method for spiking neural networks using the symmetric STDP rule
|
Hao, Yunzhe
|
|
|
121 |
C |
p. 387-395
|
artikel
|
| 2 |
Adaptive fault-tolerant consensus for a class of leader-following systems using neural network learning strategy
|
Jin, Xiaozheng
|
|
|
121 |
C |
p. 474-483
|
artikel
|
| 3 |
Adaptive latent similarity learning for multi-view clustering
|
Xie, Deyan
|
|
|
121 |
C |
p. 409-418
|
artikel
|
| 4 |
An analysis of training and generalization errors in shallow and deep networks
|
Mhaskar, H.N.
|
|
|
121 |
C |
p. 229-241
|
artikel
|
| 5 |
A sparse deep belief network with efficient fuzzy learning framework
|
Wang, Gongming
|
|
|
121 |
C |
p. 430-440
|
artikel
|
| 6 |
A waiting-time-based event-triggered scheme for stabilization of complex-valued neural networks
|
Wang, Xiaohong
|
|
|
121 |
C |
p. 329-338
|
artikel
|
| 7 |
Centralized/decentralized event-triggered pinning synchronization of stochastic coupled networks with noise and incomplete transitional rate
|
Dong, Hailing
|
|
|
121 |
C |
p. 10-20
|
artikel
|
| 8 |
Current Events
|
|
|
|
121 |
C |
p. I
|
artikel
|
| 9 |
Deep CovDenseSNN: A hierarchical event-driven dynamic framework with spiking neurons in noisy environment
|
Xu, Qi
|
|
|
121 |
C |
p. 512-519
|
artikel
|
| 10 |
Deep learning and deep knowledge representation in Spiking Neural Networks for Brain-Computer Interfaces
|
Kumarasinghe, Kaushalya
|
|
|
121 |
C |
p. 169-185
|
artikel
|
| 11 |
Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets
|
Varkarakis, Viktor
|
|
|
121 |
C |
p. 101-121
|
artikel
|
| 12 |
Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence
|
Abderrahmane, Nassim
|
|
|
121 |
C |
p. 366-386
|
artikel
|
| 13 |
Distinct role of flexible and stable encodings in sequential working memory
|
Lee, Hyeonsu
|
|
|
121 |
C |
p. 419-429
|
artikel
|
| 14 |
Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence
|
Brito da Silva, Leonardo Enzo
|
|
|
121 |
C |
p. 208-228
|
artikel
|
| 15 |
Dynamic behaviors of the FitzHugh–Nagumo neuron model with state-dependent impulsive effects
|
He, Zhilong
|
|
|
121 |
C |
p. 497-511
|
artikel
|
| 16 |
Editorial Board
|
|
|
|
121 |
C |
p. ii
|
artikel
|
| 17 |
Embedding topological features into convolutional neural network salient object detection
|
Zhou, Lecheng
|
|
|
121 |
C |
p. 308-318
|
artikel
|
| 18 |
Event-driven implementation of deep spiking convolutional neural networks for supervised classification using the SpiNNaker neuromorphic platform
|
Patiño-Saucedo, Alberto
|
|
|
121 |
C |
p. 319-328
|
artikel
|
| 19 |
Event-triggered passivity and synchronization of delayed multiple-weighted coupled reaction–diffusion neural networks with non-identical nodes
|
Lin, Shanrong
|
|
|
121 |
C |
p. 259-275
|
artikel
|
| 20 |
Finite-time resilient H ∞ state estimation for discrete-time delayed neural networks under dynamic event-triggered mechanism
|
Liu, Yufei
|
|
|
121 |
C |
p. 356-365
|
artikel
|
| 21 |
Gated spiking neural network using Iterative Free-Energy Optimization and rank-order coding for structure learning in memory sequences (INFERNO GATE)
|
Pitti, Alexandre
|
|
|
121 |
C |
p. 242-258
|
artikel
|
| 22 |
Growing to Meet the Publishing Demands of the Deep Learning Era
|
|
|
|
121 |
C |
p. xv-xvi
|
artikel
|
| 23 |
How are response properties in the middle temporal area related to inference on visual motion patterns?
|
Rezai, Omid
|
|
|
121 |
C |
p. 122-131
|
artikel
|
| 24 |
Image denoising using deep CNN with batch renormalization
|
Tian, Chunwei
|
|
|
121 |
C |
p. 461-473
|
artikel
|
| 25 |
Indirect and direct training of spiking neural networks for end-to-end control of a lane-keeping vehicle
|
Bing, Zhenshan
|
|
|
121 |
C |
p. 21-36
|
artikel
|
| 26 |
INN/ENNS/JNNS - Membership Applic. Form
|
|
|
|
121 |
C |
p. III
|
artikel
|
| 27 |
Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection
|
Razzak, Imran
|
|
|
121 |
C |
p. 441-451
|
artikel
|
| 28 |
Interfering with a memory without erasing its trace
|
Lange, Gesa
|
|
|
121 |
C |
p. 339-355
|
artikel
|
| 29 |
Label-activating framework for zero-shot learning
|
Liu, Yang
|
|
|
121 |
C |
p. 1-9
|
artikel
|
| 30 |
List of Editorial Board Members
|
|
|
|
121 |
C |
p. iii-ix
|
artikel
|
| 31 |
Modeling place cells and grid cells in multi-compartment environments: Entorhinal–hippocampal loop as a multisensory integration circuit
|
Li, Tianyi
|
|
|
121 |
C |
p. 37-51
|
artikel
|
| 32 |
Multi-output parameter-insensitive kernel twin SVR model
|
Li, Yanmeng
|
|
|
121 |
C |
p. 276-293
|
artikel
|
| 33 |
MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation
|
Ibtehaz, Nabil
|
|
|
121 |
C |
p. 74-87
|
artikel
|
| 34 |
Named entity recognition in electronic health records using transfer learning bootstrapped Neural Networks
|
Gligic, Luka
|
|
|
121 |
C |
p. 132-139
|
artikel
|
| 35 |
Neural Networks Referees in 2019
|
|
|
|
121 |
C |
p. x-xiv
|
artikel
|
| 36 |
On the validity of memristor modeling in the neural network literature
|
Pershin, Yuriy V.
|
|
|
121 |
C |
p. 52-56
|
artikel
|
| 37 |
Operation-aware Neural Networks for user response prediction
|
Yang, Yi
|
|
|
121 |
C |
p. 161-168
|
artikel
|
| 38 |
Privacy-enhanced multi-party deep learning
|
Gong, Maoguo
|
|
|
121 |
C |
p. 484-496
|
artikel
|
| 39 |
Recognition of words from brain-generated signals of speech-impaired people: Application of autoencoders as a neural Turing machine controller in deep neural networks
|
Boloukian, Behzad
|
|
|
121 |
C |
p. 186-207
|
artikel
|
| 40 |
Rethinking the performance comparison between SNNS and ANNS
|
Deng, Lei
|
|
|
121 |
C |
p. 294-307
|
artikel
|
| 41 |
Sliding mode control of neural networks via continuous or periodic sampling event-triggering algorithm
|
Wang, Shiqin
|
|
|
121 |
C |
p. 140-147
|
artikel
|
| 42 |
Spiking Neural Networks and online learning: An overview and perspectives
|
Lobo, Jesus L.
|
|
|
121 |
C |
p. 88-100
|
artikel
|
| 43 |
Synchronization in an array of coupled neural networks with delayed impulses: Average impulsive delay method
|
Jiang, Bangxin
|
|
|
121 |
C |
p. 452-460
|
artikel
|
| 44 |
The GH-EXIN neural network for hierarchical clustering
|
Cirrincione, Giansalvo
|
|
|
121 |
C |
p. 57-73
|
artikel
|
| 45 |
Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning
|
Roy, Deboleena
|
|
|
121 |
C |
p. 148-160
|
artikel
|
| 46 |
Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance
|
Sayeed, Alqamah
|
|
|
121 |
C |
p. 396-408
|
artikel
|
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