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Qiang Yu
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Precise-spike-driven synaptic plasticity: Learning hetero-association of spatiotemporal spike patterns
Q Yu, H Tang, KC Tan, H Li
Plos one 8 (11), e78318, 2013
1982013
Rapid feedforward computation by temporal encoding and learning with spiking neurons
Q Yu, H Tang, KC Tan, H Li
IEEE transactions on neural networks and learning systems 24 (10), 1539-1552, 2013
1632013
A brain-inspired spiking neural network model with temporal encoding and learning
Q Yu, H Tang, KC Tan, H Yu
Neurocomputing 138, 3-13, 2014
1362014
A spiking neural network system for robust sequence recognition
Q Yu, R Yan, H Tang, KC Tan, H Li
IEEE Transactions on Neural Networks and Learning Systems 27 (3), 621 - 635, 2016
902016
Temporal coding of local spectrogram features for robust sound recognition
J Dennis, Q Yu, H Tang, HD Tran, H Li
2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013
682013
Spike timing or rate? Neurons learn to make decisions for both through threshold-driven plasticity
Q Yu, H Li, KC Tan
IEEE transactions on cybernetics 49 (6), 2178-2189, 2019
652019
Numerical spiking neural P systems
T Wu, L Pan, Q Yu, KC Tan
IEEE Transactions on Neural Networks and Learning Systems 32 (6), 2443-2457, 2020
522020
Constructing accurate and efficient deep spiking neural networks with double-threshold and augmented schemes
Q Yu, C Ma, S Song, G Zhang, J Dang, KC Tan
IEEE Transactions on Neural Networks and Learning Systems 33 (4), 1714-1726, 2021
442021
Robust environmental sound recognition with sparse key-point encoding and efficient multi-spike learning
Q Yu, Y Yao, L Wang, H Tang, J Dang, KC Tan
IEEE Transactions on Neural Networks and Learning Systems, 2020
242020
Pattern recognition computation in a spiking neural network with temporal encoding and learning
Q Yu, KC Tan, H Tang
The 2012 International Joint Conference on Neural Networks (IJCNN), 1-7, 2012
232012
Neuromorphic cognitive systems
Q Yu, H Tang, J Hu, KC Tan
A Learning and Memory Centered Approach, 2017
202017
Gender-aware CNN-BLSTM for speech emotion recognition
L Zhang, L Wang, J Dang, L Guo, Q Yu
Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018
192018
Toward efficient processing and learning with spikes: New approaches for multispike learning
Q Yu, S Li, H Tang, L Wang, J Dang, KC Tan
IEEE Transactions on Cybernetics 52 (3), 1364-1376, 2020
162020
Fast and accurate classification with a multi-spike learning algorithm for spiking neurons.
R Xiao, Q Yu, R Yan, H Tang
IJCAI, 1445-1451, 2019
162019
Temporal dependent local learning for deep spiking neural networks
C Ma, J Xu, Q Yu
2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021
112021
Synaptic learning with augmented spikes
Q Yu, S Song, C Ma, L Pan, KC Tan
IEEE Transactions on Neural Networks and Learning Systems 33 (3), 1134-1146, 2021
112021
Temporal encoding and multispike learning framework for efficient recognition of visual patterns
Q Yu, S Song, C Ma, J Wei, S Chen, KC Tan
IEEE Transactions on Neural Networks and Learning Systems 33 (8), 3387-3399, 2021
102021
Learning real-world stimuli by single-spike coding and tempotron rule
H Tang, Q Yu, KC Tan
The 2012 International Joint Conference on Neural Networks (IJCNN), 1-6, 2012
102012
Deep spike learning with local classifiers
C Ma, R Yan, Z Yu, Q Yu
IEEE Transactions on Cybernetics, 2022
92022
Event-driven simulation of the tempotron spiking neuron
B Zhao, Q Yu, R Ding, S Chen, H Tang
2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings …, 2014
92014
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