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2020 – today
- 2024
[j107]Yongduan Song
, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-ming Cheung:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 19(1): 24-77 (2024)- [j106]Chaofei Hong, Mengwen Yuan, Mengxiao Zhang, Xiao Wang, Chengjun Zhang, Jiaxin Wang, Gang Pan, Huajin Tang:
SPAIC: A Spike-Based Artificial Intelligence Computing Framework. IEEE Comput. Intell. Mag. 19(1): 51-65 (2024) - [j105]Lei Deng, Huajin Tang, Kaushik Roy:
Editorial: Understanding and bridging the gap between neuromorphic computing and machine learning, volume II. Frontiers Comput. Neurosci. 18 (2024) - [j104]Mengwen Yuan, Chengjun Zhang, Ziming Wang, Huixiang Liu, Gang Pan, Huajin Tang:
Trainable Spiking-YOLO for low-latency and high-performance object detection. Neural Networks 172: 106092 (2024) - [j103]Hongze Sun, Rui Liu, Wuque Cai, Jun Wang, Yue Wang, Huajin Tang, Yan Cui, Dezhong Yao, Daqing Guo:
Reliable object tracking by multimodal hybrid feature extraction and transformer-based fusion. Neural Networks 178: 106493 (2024) - [j102]Shibo Zhou, Bo Yang, Mengwen Yuan, Runhao Jiang, Rui Yan, Gang Pan, Huajin Tang:
Enhancing SNN-based spatio-temporal learning: A benchmark dataset and Cross-Modality Attention model. Neural Networks 180: 106677 (2024) - [j101]Guoqi Li, Lei Deng, Huajin Tang, Gang Pan, Yonghong Tian, Kaushik Roy, Wolfgang Maass:
Brain-Inspired Computing: A Systematic Survey and Future Trends. Proc. IEEE 112(6): 544-584 (2024) - [j100]Huajin Tang:
Editorial IEEE Transactions on Cognitive and Developmental Systems. IEEE Trans. Cogn. Dev. Syst. 16(1): 3 (2024) - [j99]Shuang Lian, Jiangrong Shen, Ziming Wang, Huajin Tang:
IM-LIF: Improved Neuronal Dynamics With Attention Mechanism for Direct Training Deep Spiking Neural Network. IEEE Trans. Emerg. Top. Comput. Intell. 8(2): 2075-2085 (2024) - [j98]Houzhan Zhang, Rong Xiao, Jiaxin Li, Chuangye Yan, Huajin Tang:
A High-Precision LiDAR-Inertial Odometry via Invariant Extended Kalman Filtering and Efficient Surfel Mapping. IEEE Trans. Instrum. Meas. 73: 1-11 (2024) - [j97]Qiugang Zhan, Guisong Liu, Xiurui Xie, Ran Tao, Malu Zhang, Huajin Tang:
Spiking Transfer Learning From RGB Image to Neuromorphic Event Stream. IEEE Trans. Image Process. 33: 4274-4287 (2024) - [j96]Qi Xu, Yaxin Li, Jiangrong Shen, Pingping Zhang, Jian K. Liu, Huajin Tang, Gang Pan:
Hierarchical Spiking-Based Model for Efficient Image Classification With Enhanced Feature Extraction and Encoding. IEEE Trans. Neural Networks Learn. Syst. 35(7): 9277-9285 (2024) - [j95]Lang Qin, Ziming Wang, Rui Yan, Huajin Tang:
Attention-Based Deep Spiking Neural Networks for Temporal Credit Assignment Problems. IEEE Trans. Neural Networks Learn. Syst. 35(8): 10301-10311 (2024) - [j94]Xiurui Xie, Bei Yu, Guisong Liu, Qiugang Zhan, Huajin Tang:
Effective Active Learning Method for Spiking Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12373-12382 (2024) - [c73]Gehua Ma, He Wang, Jingyuan Zhao, Rui Yan, Huajin Tang:
Successive POI Recommendation via Brain-Inspired Spatiotemporal Aware Representation. AAAI 2024: 574-582 - [c72]Jiangrong Shen, Wenyao Ni, Qi Xu, Huajin Tang:
Efficient Spiking Neural Networks with Sparse Selective Activation for Continual Learning. AAAI 2024: 611-619 - [c71]Jianing Han, Jiangrong Shen, Qi Xu, Jian Liu, Huajin Tang:
The Balanced Multi-Modal Spiking Neural Networks with Online Loss Adjustment and Time Alignment. ICME 2024: 1-6 - [c70]Limei Liang, Runhao Jiang, Huajin Tang, Rui Yan:
An Event-based Feature Representation Method for Event Stream Classification using Deep Spiking Neural Networks. IJCNN 2024: 1-8 - [c69]Haosong Qi, Shuang Lian, Xu Li, Huajin Tang:
Adaptive Multi-Level Firing for Direct Training Deep Spiking Neural Networks. IJCNN 2024: 1-8 - [c68]Panpan Yang, Ziming Wang, Huajin Tang, Rui Yan:
Multi-scale Harmonic Mean Time Surfaces for Event-based Object Classification. IJCNN 2024: 1-8 - [c67]Zehao Chen, Zhan Lu, De Ma, Huajin Tang, Xudong Jiang, Qian Zheng, Gang Pan:
Event-ID: Intrinsic Decomposition Using an Event Camera. ACM Multimedia 2024: 10095-10104 - [i33]Qi Xu, Yuyuan Gao, Jiangrong Shen, Yaxin Li, Xuming Ran, Huajin Tang, Gang Pan:
Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks. CoRR abs/2401.03719 (2024) - [i32]Zexiang Yi, Jing Lian, Yunliang Qi, Zhaofei Yu, Huajin Tang, Yide Ma, Jizhao Liu:
Deep Pulse-Coupled Neural Networks. CoRR abs/2401.08649 (2024) - [i31]Ziming Wang, Ziling Wang, Huaning Li, Lang Qin, Runhao Jiang, De Ma, Huajin Tang:
EAS-SNN: End-to-End Adaptive Sampling and Representation for Event-based Detection with Recurrent Spiking Neural Networks. CoRR abs/2403.12574 (2024) - [i30]Lang Qin, Ziming Wang, Runhao Jiang, Rui Yan, Huajin Tang:
GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL. CoRR abs/2404.15597 (2024) - [i29]MHD Anas Alsakkal, Runze Wang, Jayawan H. B. Wijekoon, Huajin Tang:
Application based Evaluation of an Efficient Spike-Encoder, "Spiketrum". CoRR abs/2405.15927 (2024) - [i28]Hongze Sun, Rui Liu, Wuque Cai, Jun Wang, Yue Wang, Huajin Tang, Yan Cui, Dezhong Yao, Daqing Guo:
Reliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion. CoRR abs/2405.17903 (2024) - [i27]Jiangrong Shen, Wenyao Ni, Qi Xu, Gang Pan, Huajin Tang:
Context Gating in Spiking Neural Networks: Achieving Lifelong Learning through Integration of Local and Global Plasticity. CoRR abs/2406.01883 (2024) - [i26]Qiugang Zhan, Jinbo Cao, Xiurui Xie, Malu Zhang, Huajin Tang, Guisong Liu:
SFedCA: Credit Assignment-Based Active Client Selection Strategy for Spiking Federated Learning. CoRR abs/2406.12200 (2024) - [i25]Yangfan Hu, Qian Zheng, Guoqi Li, Huajin Tang, Gang Pan:
Toward Large-scale Spiking Neural Networks: A Comprehensive Survey and Future Directions. CoRR abs/2409.02111 (2024) - [i24]Weixing Zhang, Zongrui Li, De Ma, Huajin Tang, Xudong Jiang, Qian Zheng, Gang Pan:
Spiking GS: Towards High-Accuracy and Low-Cost Surface Reconstruction via Spiking Neuron-based Gaussian Splatting. CoRR abs/2410.07266 (2024) - 2023
- [j93]Wei Gao, Jiangrong Shen, Yipeng Lin, Kejun Wang, Zheng Lin, Huajin Tang, Xiaodong Chen:
Sequential sparse autoencoder for dynamic heading representation in ventral intraparietal area. Comput. Biol. Medicine 163: 107114 (2023) - [j92]Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-ming Cheung, Hussein A. Abbass:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 18(1): 17-19 (2023) - [j91]Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-Ming Cheung, Hussein A. Abbass:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 18(2): 13-15 (2023) - [j90]Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-Ming Cheung, Hussein A. Abbass:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 18(3): 10-86 (2023) - [j89]Yongduan Song, Dongrui Wu, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yiu-Ming Cheung, Hussein A. Abbass:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 18(4): 10-12 (2023) - [j88]Jianing Han, Ziming Wang, Jiangrong Shen, Huajin Tang:
Symmetric-threshold ReLU for Fast and Nearly Lossless ANN-SNN Conversion. Int. J. Autom. Comput. 20(3): 435-446 (2023) - [j87]Limiao Ning, Junfei Dong, Rong Xiao, Kay Chen Tan, Huajin Tang:
Event-driven spiking neural networks with spike-based learning. Memetic Comput. 15(2): 205-217 (2023) - [j86]Jiru Wang, Rui Yan, Huajin Tang:
Grid cell modeling with mapping representation of self-motion for path integration. Neural Comput. Appl. 35(32): 23465-23476 (2023) - [j85]Gehua Ma, Runhao Jiang, Lang Wang, Huajin Tang:
Dual memory model for experience-once task-incremental lifelong learning. Neural Networks 166: 174-187 (2023) - [j84]Gehua Ma, Rui Yan, Huajin Tang:
Exploiting noise as a resource for computation and learning in spiking neural networks. Patterns 4(10): 100831 (2023) - [j83]Huajin Tang:
Editorial IEEE Transactions on Cognitive and Developmental Systems. IEEE Trans. Cogn. Dev. Syst. 15(1): 2 (2023) - [j82]Rong Xiao, Yu Wan, Baosong Yang, Haibo Zhang, Huajin Tang, Derek F. Wong, Boxing Chen:
Towards Energy-Preserving Natural Language Understanding With Spiking Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 31: 439-447 (2023) - [j81]Guisong Liu, Wenjie Deng, Xiurui Xie, Li Huang, Huajin Tang:
Human-Level Control Through Directly Trained Deep Spiking Q-Networks. IEEE Trans. Cybern. 53(11): 7187-7198 (2023) - [j80]Yangfan Hu, Huajin Tang, Gang Pan:
Spiking Deep Residual Networks. IEEE Trans. Neural Networks Learn. Syst. 34(8): 5200-5205 (2023) - [j79]Junwei Dong, Boyu Hou, Liang Feng, Huajin Tang, Kay Chen Tan, Yew-Soon Ong:
A Cell-Based Fast Memetic Algorithm for Automated Convolutional Neural Architecture Design. IEEE Trans. Neural Networks Learn. Syst. 34(11): 9040-9053 (2023) - [c66]Jiangrong Shen, Qi Xu, Jian K. Liu, Yueming Wang, Gang Pan, Huajin Tang:
ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks. AAAI 2023: 86-93 - [c65]Qi Xu, Yaxin Li, Jiangrong Shen, Jian K. Liu, Huajin Tang, Gang Pan:
Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation. CVPR 2023: 7886-7895 - [c64]Ziming Wang, Runhao Jiang, Shuang Lian, Rui Yan, Huajin Tang:
Adaptive Smoothing Gradient Learning for Spiking Neural Networks. ICML 2023: 35798-35816 - [c63]Runhao Jiang, Jianing Han, Yingying Xue, Ping Wang, Huajin Tang:
CMCI: A Robust Multimodal Fusion Method for Spiking Neural Networks. ICONIP (3) 2023: 159-171 - [c62]Shuang Lian, Jiangrong Shen, Qianhui Liu, Ziming Wang, Rui Yan, Huajin Tang:
Learnable Surrogate Gradient for Direct Training Spiking Neural Networks. IJCAI 2023: 3002-3010 - [c61]Lang Qin, Rui Yan, Huajin Tang:
A Low Latency Adaptive Coding Spike Framework for Deep Reinforcement Learning. IJCAI 2023: 3049-3057 - [c60]Xiaocui Lin, Jiangrong Shen, Jun Wen, Huajin Tang:
Bipolar Population Threshold Encoding for Audio Recognition with Deep Spiking Neural Networks. IJCNN 2023: 1-8 - [c59]Bo Yang, Mengwen Yuan, Chengjun Zhang, Chaofei Hong, Gang Pan, Huajin Tang:
Spiking Reinforcement Learning with Memory Ability for Mapless Navigation. IROS 2023: 1-8 - [c58]Gehua Ma, Runhao Jiang, Rui Yan, Huajin Tang:
Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes. NeurIPS 2023 - [c57]Qi Xu, Yuyuan Gao, Jiangrong Shen, Yaxin Li, Xuming Ran, Huajin Tang, Gang Pan:
Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks. NeurIPS 2023 - [i23]Qi Xu, Yaxin Li, Jiangrong Shen, Jian K. Liu, Huajin Tang, Gang Pan:
Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation. CoRR abs/2304.05627 (2023) - [i22]Qi Xu, Yaxin Li, Xuanye Fang, Jiangrong Shen, Jian K. Liu, Huajin Tang, Gang Pan:
Biologically inspired structure learning with reverse knowledge distillation for spiking neural networks. CoRR abs/2304.09500 (2023) - [i21]Gehua Ma, Rui Yan, Huajin Tang:
Exploiting Noise as a Resource for Computation and Learning in Spiking Neural Networks. CoRR abs/2305.16044 (2023) - [i20]Jiangrong Shen, Qi Xu, Jian K. Liu, Yueming Wang, Gang Pan, Huajin Tang:
ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks. CoRR abs/2306.03693 (2023) - [i19]Xundong Wu, Pengfei Zhao, Zilin Yu, Lei Ma, Ka-Wa Yip, Huajin Tang, Gang Pan, Tiejun Huang:
Mitigating Communication Costs in Neural Networks: The Role of Dendritic Nonlinearity. CoRR abs/2306.11950 (2023) - [i18]Jinye Qu, Zeyu Gao, Tielin Zhang, Yanfeng Lu, Huajin Tang, Hong Qiao:
Spiking Neural Network for Ultra-low-latency and High-accurate Object Detection. CoRR abs/2306.12010 (2023) - [i17]Gehua Ma, Runhao Jiang, Rui Yan, Huajin Tang:
Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes. CoRR abs/2306.12045 (2023) - [i16]Xinyi Chen, Jibin Wu, Huajin Tang, Qinyuan Ren, Kay Chen Tan:
Unleashing the Potential of Spiking Neural Networks for Sequential Modeling with Contextual Embedding. CoRR abs/2308.15150 (2023) - [i15]Huajin Tang, Pengjie Gu, Jayawan H. B. Wijekoon, MHD Anas Alsakkal, Ziming Wang, Jiangrong Shen, Rui Yan:
Neuromorphic Auditory Perception by Neural Spiketrum. CoRR abs/2309.05430 (2023) - [i14]De Ma, Xiaofei Jin, Shichun Sun, Yitao Li, Xundong Wu, Youneng Hu, Fangchao Yang, Huajin Tang, Xiaolei Zhu, Peng Lin, Gang Pan:
Darwin3: A large-scale neuromorphic chip with a Novel ISA and On-Chip Learning. CoRR abs/2312.17582 (2023) - 2022
- [j78]Yongduan Song, Jon Garibaldi, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yew Soon Ong, Hussein A. Abbass:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 17(1): 10-12 (2022) - [j77]Yongduan Song, Jon Garibaldi, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yew Soon Ong, Hussein A. Abbass:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 17(2): 11-13 (2022) - [j76]Yongduan Song, Jon Garibaldi, Carlos A. Coello Coello, Georgios N. Yannakakis, Huajin Tang, Yew Soon Ong, Hussein A. Abbass:
CIS Publication Spotlight [Publication Spotlight]. IEEE Comput. Intell. Mag. 17(3): 11-13 (2022) - [j75]Jiaxin Li, Dengju Li, Runhao Jiang, Rong Xiao, Huajin Tang, Kay Chen Tan:
Vision-Action Semantic Associative Learning Based on Spiking Neural Networks for Cognitive Robot. IEEE Comput. Intell. Mag. 17(4): 27-38 (2022) - [j74]Shuang Lian, Qianhui Liu, Rui Yan, Gang Pan, Huajin Tang:
Training Deep Convolutional Spiking Neural Networks With Spike Probabilistic Global Pooling. Neural Comput. 34(5): 1170-1188 (2022) - [j73]Junfei Dong, Runhao Jiang, Rong Xiao, Rui Yan, Huajin Tang:
Event stream learning using spatio-temporal event surface. Neural Networks 154: 543-559 (2022) - [j72]Huajin Tang:
Editorial IEEE Transactions on Cognitive and Developmental Systems. IEEE Trans. Cogn. Dev. Syst. 14(1): 2-3 (2022) - [j71]Xiaolei Zhu, Baixin Zhao, De Ma, Huajin Tang:
An Efficient Learning Algorithm for Direct Training Deep Spiking Neural Networks. IEEE Trans. Cogn. Dev. Syst. 14(3): 847-856 (2022) - [j70]Jiaxin Li, Huajin Tang, Rui Yan:
A Hybrid Loop Closure Detection Method Based on Brain-Inspired Models. IEEE Trans. Cogn. Dev. Syst. 14(4): 1532-1543 (2022) - [j69]Qiang Yu, Shenglan Li, Huajin Tang, Longbiao Wang, Jianwu Dang, Kay Chen Tan:
Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning. IEEE Trans. Cybern. 52(3): 1364-1376 (2022) - [j68]Qiugang Zhan, Guisong Liu, Xiurui Xie, Guolin Sun, Huajin Tang:
Effective Transfer Learning Algorithm in Spiking Neural Networks. IEEE Trans. Cybern. 52(12): 13323-13335 (2022) - [j67]Qi Xu, Jiangrong Shen, Xuming Ran, Huajin Tang, Gang Pan, Jian K. Liu:
Robust Transcoding Sensory Information With Neural Spikes. IEEE Trans. Neural Networks Learn. Syst. 33(5): 1935-1946 (2022) - [c56]Qianhui Liu, Dong Xing, Lang Feng, Huajin Tang, Gang Pan:
Event-Based Multimodal Spiking Neural Network with Attention Mechanism. ICASSP 2022: 8922-8926 - [c55]Peigen Liu, Guang Chen, Zhijun Li, Huajin Tang, Alois C. Knoll:
Learning Local Event-based Descriptor for Patch-based Stereo Matching. ICRA 2022: 412-418 - [c54]Lang Feng, Qianhui Liu, Huajin Tang, De Ma, Gang Pan:
Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks. IJCAI 2022: 2471-2477 - [i13]Guisong Liu, Wenjie Deng, Xiurui Xie, Li Huang, Huajin Tang:
Human-Level Control through Directly-Trained Deep Spiking Q-Networks. CoRR abs/2201.07211 (2022) - [i12]Ziming Wang, Shuang Lian, Yuhao Zhang, Xiaoxin Cui, Rui Yan, Huajin Tang:
Towards Lossless ANN-SNN Conversion under Ultra-Low Latency with Dual-Phase Optimization. CoRR abs/2205.07473 (2022) - [i11]Chaofei Hong, Mengwen Yuan, Mengxiao Zhang, Xiao Wang, Chengjun Zhang, Jiaxin Wang, Gang Pan, Zhaohui Wu, Huajin Tang:
SPAIC: A Spike-based Artificial Intelligence Computing Framework. CoRR abs/2207.12750 (2022) - [i10]Lang Feng, Qianhui Liu, Huajin Tang, De Ma, Gang Pan:
Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks. CoRR abs/2210.06386 (2022) - [i9]Lang Qin, Rui Yan, Huajin Tang:
A Low Latency Adaptive Coding Spiking Framework for Deep Reinforcement Learning. CoRR abs/2211.11760 (2022) - 2021
- [j66]Lei Deng, Huajin Tang, Kaushik Roy:
Editorial: Understanding and Bridging the Gap Between Neuromorphic Computing and Machine Learning. Frontiers Comput. Neurosci. 15: 665662 (2021) - [j65]Jeffrey L. Krichmar, James Leland Olds, Juan Vicente Sánchez-Andrés, Huajin Tang:
Editorial: Explainable Artificial Intelligence and Neuroscience: Cross-Disciplinary Perspectives. Frontiers Neurorobotics 15: 731733 (2021) - [j64]Runhao Jiang, Jie Zhang, Rui Yan, Huajin Tang:
Few-Shot Learning in Spiking Neural Networks by Multi-Timescale Optimization. Neural Comput. 33(9): 2439-2472 (2021) - [j63]Suogui Dang, Yining Wu, Rui Yan, Huajin Tang:
Why grid cells function as a metric for space. Neural Networks 142: 128-137 (2021) - [j62]Yixuan Wang, Yang Xu, Rui Yan, Huajin Tang:
Deep Spiking Neural Networks With Binary Weights for Object Recognition. IEEE Trans. Cogn. Dev. Syst. 13(3): 514-523 (2021) - [j61]Guang Chen, Zhongcong Xu, Zhijun Li, Huajin Tang, Sanqing Qu, Kejia Ren, Alois C. Knoll:
A Novel Illumination-Robust Hand Gesture Recognition System With Event-Based Neuromorphic Vision Sensor. IEEE Trans Autom. Sci. Eng. 18(2): 508-520 (2021) - [j60]Guang Chen, Peigen Liu, Zhengfa Liu, Huajin Tang, Lin Hong, Jinhu Dong, Jörg Conradt, Alois C. Knoll:
NeuroAED: Towards Efficient Abnormal Event Detection in Visual Surveillance With Neuromorphic Vision Sensor. IEEE Trans. Inf. Forensics Secur. 16: 923-936 (2021) - [j59]Qiang Yu, Yanli Yao, Longbiao Wang, Huajin Tang, Jianwu Dang, Kay Chen Tan:
Robust Environmental Sound Recognition With Sparse Key-Point Encoding and Efficient Multispike Learning. IEEE Trans. Neural Networks Learn. Syst. 32(2): 625-638 (2021) - [c53]Zehao Chen, Qian Zheng, Peisong Niu, Huajin Tang, Gang Pan:
Indoor Lighting Estimation Using an Event Camera. CVPR 2021: 14760-14770 - [c52]Qianhui Liu, Dong Xing, Huajin Tang, De Ma, Gang Pan:
Event-based Action Recognition Using Motion Information and Spiking Neural Networks. IJCAI 2021: 1743-1749 - 2020
- [j58]Jiru Wang, Rui Yan, Huajin Tang:
Multi-Scale Extension in an Entorhinal-Hippocampal Model for Cognitive Map Building. Frontiers Neurorobotics 14: 592057 (2020) - [j57]Xiping Ju, Biao Fang, Rui Yan, Xiaoliang Xu, Huajin Tang:
An FPGA Implementation of Deep Spiking Neural Networks for Low-Power and Fast Classification. Neural Comput. 32(1): 182-204 (2020) - [j56]Qi Xu, Jianxin Peng, Jiangrong Shen, Huajin Tang, Gang Pan:
Deep CovDenseSNN: A hierarchical event-driven dynamic framework with spiking neurons in noisy environment. Neural Networks 121: 512-519 (2020) - [j55]Guang Chen, Hu Cao, Jörg Conradt, Huajin Tang, Florian Röhrbein, Alois C. Knoll:
Event-Based Neuromorphic Vision for Autonomous Driving: A Paradigm Shift for Bio-Inspired Visual Sensing and Perception. IEEE Signal Process. Mag. 37(4): 34-49 (2020) - [j54]Rong Xiao, Huajin Tang, Yuhao Ma, Rui Yan, Garrick Orchard:
An Event-Driven Categorization Model for AER Image Sensors Using Multispike Encoding and Learning. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3649-3657 (2020) - [j53]Qianhui Liu, Gang Pan, Haibo Ruan, Dong Xing, Qi Xu, Huajin Tang:
Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons. IEEE Trans. Neural Networks Learn. Syst. 31(12): 5300-5311 (2020) - [c51]Qianhui Liu, Haibo Ruan, Dong Xing, Huajin Tang, Gang Pan:
Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks. AAAI 2020: 1308-1315 - [c50]Junwei Lu, Junfei Dong, Rui Yan, Huajin Tang:
An Event-based Categorization Model Using Spatio-temporal Features in a Spiking Neural Network. ICACI 2020: 385-390 - [c49]Biao Fang, Yuhao Zhang, Rui Yan, Huajin Tang:
Spike Trains Encoding Optimization for Spiking Neural Networks Implementation in FPGA. ICACI 2020: 412-418 - [c48]Jianxin Peng, Suogui Dang, Rui Yan, Huajin Tang:
A Novel Mathematic Entorhinal-Hippocampal System Building Cognitive Map. ICONIP (2) 2020: 3-14 - [c47]Xianglan Wen, Pengjie Gu, Rui Yan, Huajin Tang:
Deep Spiking Neural Network Using Spatio-temporal Backpropagation with Variable Resistance. IJCNN 2020: 1-7 - [c46]Tang Tang, Runhao Jiang, Rui Yan, Huajin Tang:
An Event-Driven Object Recognition Model Using Activated Connected Domain Detection. SSCI 2020: 3049-3056 - [i8]Qianhui Liu, Haibo Ruan, Dong Xing, Huajin Tang, Gang Pan:
Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks. CoRR abs/2002.06199 (2020) - [i7]Qiang Yu, Shenglan Li, Huajin Tang, Longbiao Wang, Jianwu Dang, Kay Chen Tan:
Towards Efficient Processing and Learning with Spikes: New Approaches for Multi-Spike Learning. CoRR abs/2005.00723 (2020)
2010 – 2019
- 2019
- [j52]Yijun Liu, Zuoteng Xu, Wujian Ye, Ziwen Zhang, Shaowei Weng, Chin-Chen Chang, Huajin Tang:
Image Neural Style Transfer With Preserving the Salient Regions. IEEE Access 7: 40027-40037 (2019) - [j51]Suogui Dang, Jiru Wang, Rui Yan, Huajin Tang:
SeqDLF: Deep Local Feature-Based Image Sequence Representation for Visual Loop Closure Detection. Aust. J. Intell. Inf. Process. Syst. 16(2): 9-18 (2019) - [j50]Mengwen Yuan, Xi Wu, Rui Yan, Huajin Tang:
Reinforcement Learning in Spiking Neural Networks with Stochastic and Deterministic Synapses. Neural Comput. 31(12): 2368-2389 (2019) - [j49]Xi Wu, Yixuan Wang, Huajin Tang, Rui Yan:
A structure-time parallel implementation of spike-based deep learning. Neural Networks 113: 72-78 (2019) - [j48]Jiru Wang, Vui Ann Shim, Rui Yan, Huajin Tang, Fuchun Sun:
Automatic Object Searching and Behavior Learning for Mobile Robots in Unstructured Environment by Deep Belief Networks. IEEE Trans. Cogn. Dev. Syst. 11(3): 395-404 (2019) - [j47]Guilin Yang, I-Ming Chen, Chin-Yin Chen, Huajin Tang, Chi Zhang:
Guest Editorial Special Section on Emerging Information Sharing and Design Technologies on Robotics and Mechatronics Systems for Intelligent Manufacturing. IEEE Trans. Ind. Informatics 15(3): 1643-1646 (2019) - [c45]Qiang Yu, Yanli Yao, Longbiao Wang, Huajin Tang, Jianwu Dang:
A Multi-spike Approach for Robust Sound Recognition. ICASSP 2019: 890-894 - [c44]Dengju Li, Rui Yan, Xiaoliang Xu, Huajin Tang:
Dance to Music Expressively: A Brain-Inspired System Based on Audio-Semantic Model for Cognitive Development of Robots. ICONIP (4) 2019: 433-440 - [c43]Pengjie Gu, Rong Xiao, Gang Pan, Huajin Tang:
STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks. IJCAI 2019: 1366-1372 - [c42]Rong Xiao, Qiang Yu, Rui Yan, Huajin Tang:
Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons. IJCAI 2019: 1445-1451 - [c41]Yan Dai, Mengwen Yuan, Huajin Tang, Rui Yan:
A temporal encoding method based on expansion representation. IJCNN 2019: 1-8 - [c40]Zeyang Song, Xi Wu, Mengwen Yuan, Huajin Tang:
An Unsupervised Spiking Deep Neural Network for Object Recognition. ISNN (2) 2019: 361-370 - [c39]Hanxiao Qian, Pengjie Gu, Rui Yan, Huajin Tang:
Robust Multipitch Estimation of Piano Sounds Using Deep Spiking Neural Networks. SSCI 2019: 2335-2341 - [e2]Huchuan Lu, Huajin Tang, Zhanshan Wang:
Advances in Neural Networks - ISNN 2019 - 16th International Symposium on Neural Networks, ISNN 2019, Moscow, Russia, July 10-12, 2019, Proceedings, Part I. Lecture Notes in Computer Science 11554, Springer 2019, ISBN 978-3-030-22795-1 [contents] - [e1]Huchuan Lu, Huajin Tang, Zhanshan Wang:
Advances in Neural Networks - ISNN 2019 - 16th International Symposium on Neural Networks, ISNN 2019, Moscow, Russia, July 10-12, 2019, Proceedings, Part II. Lecture Notes in Computer Science 11555, Springer 2019, ISBN 978-3-030-22807-1 [contents] - [i6]Qiang Yu, Yanli Yao, Longbiao Wang, Huajin Tang, Jianwu Dang, Kay Chen Tan:
Robust Environmental Sound Recognition with Sparse Key-point Encoding and Efficient Multi-spike Learning. CoRR abs/1902.01094 (2019) - [i5]Qianhui Liu, Gang Pan, Haibo Ruan, Dong Xing, Qi Xu, Huajin Tang:
Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons. CoRR abs/1911.08261 (2019) - 2018
- [j46]Rong Xiao, Huajin Tang, Pengjie Gu, Xiaoliang Xu:
Spike-based encoding and learning of spectrum features for robust sound recognition. Neurocomputing 313: 65-73 (2018) - [j45]Huajin Tang, Tiejun Huang, Jeffrey L. Krichmar, Garrick Orchard, Arindam Basu:
Guest Editorial Special Issue on Neuromorphic Computing and Cognitive Systems. IEEE Trans. Cogn. Dev. Syst. 10(2): 122-125 (2018) - [j44]Huajin Tang, Rui Yan, Kay Chen Tan:
Cognitive Navigation by Neuro-Inspired Localization, Mapping, and Episodic Memory. IEEE Trans. Cogn. Dev. Syst. 10(3): 751-761 (2018) - [j43]Huajin Tang, Rui Yan, Kay Chen Tan:
Corrections to "Cognitive Navigation by Neuro-Inspired Localization, Mapping, and Episodic Memory". IEEE Trans. Cogn. Dev. Syst. 10(4): 1165 (2018) - [j42]Xi Peng, Canyi Lu, Zhang Yi, Huajin Tang:
Connections Between Nuclear-Norm and Frobenius-Norm-Based Representations. IEEE Trans. Neural Networks Learn. Syst. 29(1): 218-224 (2018) - [j41]Yajing Zheng, Shixin Li, Rui Yan, Huajin Tang, Kay Chen Tan:
Sparse Temporal Encoding of Visual Features for Robust Object Recognition by Spiking Neurons. IEEE Trans. Neural Networks Learn. Syst. 29(12): 5823-5833 (2018) - [c38]Dong Niu, Dengju Li, Rui Yan, Huajin Tang:
A Gesture Recognition Method Based on Spiking Neural Networks for Cognition Development. ICONIP (1) 2018: 582-593 - [c37]Yu Qi, Jiangrong Shen, Yueming Wang, Huajin Tang, Hang Yu, Zhaohui Wu, Gang Pan:
Jointly Learning Network Connections and Link Weights in Spiking Neural Networks. IJCAI 2018: 1597-1603 - [c36]Qi Xu, Yu Qi, Hang Yu, Jiangrong Shen, Huajin Tang, Gang Pan:
CSNN: An Augmented Spiking based Framework with Perceptron-Inception. IJCAI 2018: 1646-1652 - [c35]Yu Miao, Huajin Tang, Gang Pan:
A Supervised Multi-Spike Learning Algorithm for Spiking Neural Networks. IJCNN 2018: 1-7 - [i4]Yangfan Hu, Huajin Tang, Yueming Wang, Gang Pan:
Spiking Deep Residual Network. CoRR abs/1805.01352 (2018) - 2017
- [b1]Qiang Yu, Huajin Tang, Jun Hu, Kay Chen Tan:
Neuromorphic Cognitive Systems - A Learning and Memory Centered Approach. Intelligent Systems Reference Library 126, Springer 2017, ISBN 978-3-319-55308-5, pp. 1-172 - [j40]Sun-Chun Zhou, Rui Yan, Jia-Xin Li, Ying-Ke Chen, Huajin Tang:
A brain-inspired SLAM system based on ORB features. Int. J. Autom. Comput. 14(5): 564-575 (2017) - [j39]Huajin Tang, Weiwei Huang, Aditya Narayanamoorthy, Rui Yan:
Cognitive memory and mapping in a brain-like system for robotic navigation. Neural Networks 87: 27-37 (2017) - [j38]Xi Peng, Zhiding Yu, Zhang Yi, Huajin Tang:
Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering. IEEE Trans. Cybern. 47(4): 1053-1066 (2017) - [j37]Zhaohui Wu, Ryad Benosman, Huajin Tang, Shih-Chii Liu:
Guest Editorial Learning in Neuromorphic Systems and Cyborg Intelligence. IEEE Trans. Neural Networks Learn. Syst. 28(4): 774-777 (2017) - [j36]Xi Peng, Bo Zhao, Rui Yan, Huajin Tang, Zhang Yi:
Bag of Events: An Efficient Probability-Based Feature Extraction Method for AER Image Sensors. IEEE Trans. Neural Networks Learn. Syst. 28(4): 791-803 (2017) - [c34]Yuhao Ma, Rong Xiao, Huajin Tang:
An Event-Driven Computational System with Spiking Neurons for Object Recognition. ICONIP (6) 2017: 453-461 - [c33]Na Guo, Rong Xiao, Shaobing Gao, Huajin Tang:
A neurally inspired pattern recognition approach with latency-phase encoding and precise-spike-driven rule in spiking neural network. CIS/RAM 2017: 484-489 - [c32]Yang Xu, Huajin Tang, Jinwei Xing, Hongying Li:
Spike trains encoding and threshold rescaling method for deep spiking neural networks. SSCI 2017: 1-6 - 2016
- [j35]Jun Hu, Huajin Tang, Kay Chen Tan, Haizhou Li:
How the Brain Formulates Memory: A Spatio-Temporal Model Research Frontier. IEEE Comput. Intell. Mag. 11(2): 56-68 (2016) - [j34]Hussein A. Abbass, Huajin Tang, Meng-Hiot Lim:
Editorial. Memetic Comput. 8(1): 1-2 (2016) - [j33]Qiang Yu, Rui Yan, Huajin Tang, Kay Chen Tan, Haizhou Li:
A Spiking Neural Network System for Robust Sequence Recognition. IEEE Trans. Neural Networks Learn. Syst. 27(3): 621-635 (2016) - [j32]Xi Peng, Huajin Tang, Lei Zhang, Zhang Yi, Shijie Xiao:
A Unified Framework for Representation-Based Subspace Clustering of Out-of-Sample and Large-Scale Data. IEEE Trans. Neural Networks Learn. Syst. 27(12): 2499-2512 (2016) - [c31]Huajin Tang, Boon Hwa Tan, Rui Yan:
Robot-to-human handover with obstacle avoidance via continuous time Recurrent Neural Network. CEC 2016: 1204-1211 - [c30]Jun Hu, Miaolong Yuan, Huajin Tang, Wei-Yun Yau:
Hebbian learning analysis of a grid cell based cognitive mapping system. CEC 2016: 1212-1218 - [c29]Rong Xiao, Rui Yan, Huajin Tang, Kay Chen Tan:
A Spiking Neural Network Model for Sound Recognition. ICCSIP 2016: 584-594 - 2015
- [j31]Xi Peng, Rui Yan, Bo Zhao, Huajin Tang, Zhang Yi:
Fast low rank representation based spatial pyramid matching for image classification. Knowl. Based Syst. 90: 14-22 (2015) - [j30]Vui Ann Shim, Chris Stephen Naveen Ranjit, Bo Tian, Miaolong Yuan, Huajin Tang:
A Simplified Cerebellar Model with Priority-based Delayed Eligibility Trace Learning for Motor Control. IEEE Trans. Auton. Ment. Dev. 7(1): 26-38 (2015) - [j29]Vui Ann Shim, Kay Chen Tan, Huajin Tang:
Adaptive Memetic Computing for Evolutionary Multiobjective Optimization. IEEE Trans. Cybern. 45(4): 610-621 (2015) - [j28]Bo Zhao, Ruoxi Ding, Shoushun Chen, Bernabé Linares-Barranco, Huajin Tang:
Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network. IEEE Trans. Neural Networks Learn. Syst. 26(9): 1963-1978 (2015) - [c28]Miaolong Yuan, Bo Tian, Vui Ann Shim, Huajin Tang, Haizhou Li:
An Entorhinal-Hippocampal Model for Simultaneous Cognitive Map Building. AAAI 2015: 586-592 - [c27]Xi Peng, Zhang Yi, Huajin Tang:
Robust Subspace Clustering via Thresholding Ridge Regression. AAAI 2015: 3827-3833 - [c26]Boon Hwa Tan, Huajin Tang:
Grasping control for a neuro-cognitive robot. RAM/CIS 2015: CIS:185-190 - [c25]Aditya Narayanamoorthy, Xi Peng, Huajin Tang:
Applying low rank representation based spatial pyramid matching in welding image classification. RAM/CIS 2015: CIS:208-211 - [i3]Xi Peng, Canyi Lu, Zhang Yi, Huajin Tang:
Connections Between Nuclear Norm and Frobenius Norm Based Representation. CoRR abs/1502.07423 (2015) - 2014
- [j27]Weiwei Huang, Huajin Tang, Bo Tian:
Vision enhanced neuro-cognitive structure for robotic spatial cognition. Neurocomputing 129: 49-58 (2014) - [j26]Huajin Tang, Kiruthika Ramanathan, Ning Ning:
Guest editorial: Special issue on brain inspired models of cognitive memory. Neurocomputing 138: 1-2 (2014) - [j25]Qiang Yu, Huajin Tang, Kay Chen Tan, Haoyong Yu:
A brain-inspired spiking neural network model with temporal encoding and learning. Neurocomputing 138: 3-13 (2014) - [j24]Miaolong Yuan, Huajin Tang, Haizhou Li:
Real-Time Keypoint Recognition Using Restricted Boltzmann Machine. IEEE Trans. Neural Networks Learn. Syst. 25(11): 2119-2126 (2014) - [c24]Bo Zhao, Qiang Yu, Ruoxi Ding, Shoushun Chen, Huajin Tang:
Event-driven simulation of the tempotron spiking neuron. BioCAS 2014: 667-670 - [c23]Bo Zhao, Shoushun Chen, Huajin Tang:
Bio-inspired categorization using event-driven feature extraction and spike-based learning. IJCNN 2014: 3845-3852 - [c22]Qiang Yu, Huajin Tang, Kay Chen Tan:
A new learning rule for classification of spatiotemporal spike patterns. IJCNN 2014: 3853-3858 - [c21]Boon Hwa Tan, Huajin Tang, Rui Yan, Jun Tani:
Flexible and robust robotic arm design and skill learning by using recurrent neural networks. IROS 2014: 522-529 - [c20]Vui Ann Shim, Bo Tian, Miaolong Yuan, Huajin Tang, Haizhou Li:
Direction-driven navigation using cognitive map for mobile robots. IROS 2014: 2639-2646 - [i2]Xi Peng, Rui Yan, Bo Zhao, Huajin Tang, Zhang Yi:
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification. CoRR abs/1409.5786 (2014) - [i1]Xi Peng, Zhang Yi, Huajin Tang:
Principal Coefficients Embedding: Theory and Algorithm. CoRR abs/1411.4419 (2014) - 2013
- [j23]Jiali Yu, Huajin Tang, Haizhou Li, Luping Shi:
Dynamical properties of continuous attractor neural network with background tuning. Neurocomputing 99: 439-447 (2013) - [j22]Jiali Yu, Huajin Tang, Haizhou Li:
Continuous attractors of discrete-time recurrent neural networks. Neural Comput. Appl. 23(1): 89-96 (2013) - [j21]Jun Hu, Huajin Tang, Kay Chen Tan, Haizhou Li, Luping Shi:
A Spike-Timing-Based Integrated Model for Pattern Recognition. Neural Comput. 25(2): 450-472 (2013) - [j20]Jiali Yu, Huajin Tang, Haizhou Li:
Dynamics Analysis of a Population Decoding Model. IEEE Trans. Neural Networks Learn. Syst. 24(3): 498-503 (2013) - [j19]Qiang Yu, Huajin Tang, Kay Chen Tan, Haizhou Li:
Rapid Feedforward Computation by Temporal Encoding and Learning With Spiking Neurons. IEEE Trans. Neural Networks Learn. Syst. 24(10): 1539-1552 (2013) - [c19]Bo Zhao, Qiang Yu, Hang Yu, Shoushun Chen, Huajin Tang:
A bio-inspired feedforward system for categorization of AER motion events. BioCAS 2013: 9-12 - [c18]Jun Hu, Huajin Tang, Kay Chen Tan:
Spiking-timing based pattern recognition with real-world visual stimuli. CCMB 2013: 23-28 - [c17]Jonathan William Dennis, Qiang Yu, Huajin Tang, Tran Huy Dat, Haizhou Li:
Temporal coding of local spectrogram features for robust sound recognition. ICASSP 2013: 803-807 - [c16]Huajin Tang, Bo Tian, Vui Ann Shim, Kay Chen Tan:
A neuro-cognitive system and its application in robotics. ICCA 2013: 406-411 - [c15]Vui Ann Shim, Chris Stephen Naveen Ranjit, Bo Tian, Huajin Tang:
A Simplified Cerebellum-Based Model for Motor Control in Brain Based Devices. ICONIP (1) 2013: 520-527 - [c14]Jun Hu, Huajin Tang, Kay Chen Tan:
A hierarchical organized memory model using spiking neurons. IJCNN 2013: 1-6 - [c13]Chin Hiong Tan, Huajin Tang, Eng Yeow Cheu, Jun Hu:
A computationally efficient associative memory model of hippocampus CA3 by spiking neurons. IJCNN 2013: 1-8 - [c12]Bo Tian, Vui Ann Shim, Miaolong Yuan, Chithra Srinivasan, Huajin Tang, Haizhou Li:
RGB-D based cognitive map building and navigation. IROS 2013: 1562-1567 - 2012
- [j18]Rui Yan, Keng Peng Tee, Yuanwei Chua, Haizhou Li, Huajin Tang:
Gesture Recognition Based on Localist Attractor Networks with Application to Robot Control [Application Notes]. IEEE Comput. Intell. Mag. 7(1): 64-74 (2012) - [j17]Eng Yeow Cheu, Jiali Yu, Chin Hiong Tan, Huajin Tang:
Synaptic conditions for auto-associative memory storage and pattern completion in Jensen et al.'s model of hippocampal area CA3. J. Comput. Neurosci. 33(3): 435-447 (2012) - [j16]Bart Baesens, Pantelis Bouboulis, Sergio Cruces, Carlotta Domeniconi, Shiro Ikeda, Xuelong Li, Patricia Melin, Vadrevu Sree Hari Rao, Björn W. Schuller, Yi Shen, Huajin Tang, Cong Wang, Jian Yang, Derong Zhao, Derong Liu:
Neural Networks and Learning Systems Come Together. IEEE Trans. Neural Networks Learn. Syst. 23(1): 1-6 (2012) - [c11]Huajin Tang, Qiang Yu, Kay Chen Tan:
Learning real-world stimuli by single-spike coding and tempotron rule. IJCNN 2012: 1-6 - [c10]Qiang Yu, Kay Chen Tan, Huajin Tang:
Pattern recognition computation in a spiking neural network with temporal encoding and learning. IJCNN 2012: 1-7 - 2011
- [j15]Huajin Tang, Haizhou Li:
Information Theoretic Learning: Reny's Entropy and Kernel Perspectives (Principe, J.; 2010) [Book Review]. IEEE Comput. Intell. Mag. 6(3): 60-62 (2011) - [c9]Huajin Tang, Weiwei Huang:
Brain Inspired Cognitive System for Learning and Memory. ICONIP (1) 2011: 477-484 - [c8]Weiwei Huang, Huajin Tang, Jiali Yu, Chin Hiong Tan:
A Neuro-cognitive Robot for Spatial Navigation. ICONIP (1) 2011: 485-492 - [c7]Chin Hiong Tan, Eng Yeow Cheu, Jun Hu, Qiang Yu, Huajin Tang:
Associative Memory Model of Hippocampus CA3 Using Spike Response Neurons. ICONIP (1) 2011: 493-500 - 2010
- [j14]Huajin Tang, Haizhou Li, Rui Yan:
Memory Dynamics in Attractor Networks with Saliency Weights. Neural Comput. 22(7): 1899-1926 (2010) - [j13]Huajin Tang, Haizhou Li, Zhang Yi:
A discrete-time neural network for optimization problems with hybrid constraints. IEEE Trans. Neural Networks 21(7): 1184-1189 (2010) - [c6]Huajin Tang, Vui Ann Shim, Kay Chen Tan, Jun Yong Chia:
Restricted Boltzmann machine based algorithm for multi-objective optimization. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c5]Rui Yan, Keng Peng Tee, Yuanwei Chua, Huajin Tang:
A gesture recognition system using Localist Attractor Networks for human-robot interaction. ROBIO 2010: 1217-1222
2000 – 2009
- 2009
- [j12]Jonathan J. Hunt, Clare E. Giacomantonio, Huajin Tang, Duncan Mortimer, Sajjida Jaffer, Vasily Vorobyov, Geoffery Ericksson, Frank Sengpiel, Geoffrey J. Goodhill:
Natural scene statistics and the structure of orientation maps in the visual cortex. NeuroImage 47(1): 157-172 (2009) - [j11]Lan Zou, Huajin Tang, Kay Chen Tan, Weinian Zhang:
Analysis of Continuous Attractors for 2-D Linear Threshold Neural Networks. IEEE Trans. Neural Networks 20(1): 175-180 (2009) - [j10]Lan Zou, Huajin Tang, Kay Chen Tan, Weinian Zhang:
Nontrivial Global Attractors in 2-D Multistable Attractor Neural Networks. IEEE Trans. Neural Networks 20(11): 1842-1851 (2009) - [c4]Rui Yan, Haizhou Li, Zhao Yang Dong, Huajin Tang:
Nonlinear control approaches for SI engine model with uncertainties. CDC 2009: 5440-5445 - 2008
- [j9]Eu Jin Teoh, Kay Chen Tan, Huajin Tang, Cheng Xiang, Chi Keong Goh:
An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem. Neurocomputing 71(7-9): 1359-1372 (2008) - 2006
- [j8]Hong Qu, Zhang Yi, Huajin Tang:
Improving local minima of columnar competitive model for TSPs. IEEE Trans. Circuits Syst. I Regul. Pap. 53-I(6): 1353-1362 (2006) - [j7]Huajin Tang, Kay Chen Tan, Eu Jin Teoh:
Dynamics analysis and analog associative memory of networks with LT neurons. IEEE Trans. Neural Networks 17(2): 409-418 (2006) - [c3]Eu Jin Teoh, Huajin Tang, Kay Chen Tan:
A Columnar Competitive Model with Simulated Annealing for Solving Combinatorial Optimization Problems. IJCNN 2006: 3254-3259 - [c2]Rui Yan, Meng Joo Er, Huajin Tang:
An Improvement on Competitive Neural Networks Applied to Image Segmentation. ISNN (2) 2006: 498-503 - 2005
- [j6]Huajin Tang, Kay Chen Tan, Weinian Zhang:
Analysis of Cyclic Dynamics for Networks of Linear Threshold Neurons. Neural Comput. 17(1): 97-114 (2005) - [j5]Kay Chen Tan, Huajin Tang, Shuzhi Sam Ge:
On parameter settings of Hopfield networks applied to traveling salesman problems. IEEE Trans. Circuits Syst. I Regul. Pap. 52-I(5): 994-1002 (2005) - [j4]Kay Chen Tan, Huajin Tang, Weinian Zhang:
Qualitative analysis for recurrent neural networks with linear threshold transfer functions. IEEE Trans. Circuits Syst. I Regul. Pap. 52-I(5): 1003-1012 (2005) - 2004
- [j3]Kay Chen Tan, Huajin Tang, Z. Yi:
Global exponential stability of discrete-time neural networks for constrained quadratic optimization. Neurocomputing 56: 399-406 (2004) - [j2]Kay Chen Tan, Huajin Tang:
New dynamical optimal learning for linear multilayer FNN. IEEE Trans. Neural Networks 15(6): 1562-1570 (2004) - [j1]Huajin Tang, Kay Chen Tan, Zhang Yi:
A columnar competitive model for solving combinatorial optimization problems. IEEE Trans. Neural Networks 15(6): 1568-1574 (2004) - [c1]Huajin Tang, Kay Chen Tan, Tong Heng Lee:
Dynamical optimal learning for FNN and its applications. FUZZ-IEEE 2004: 443-447
Coauthor Index
[j102] [j95] [c73] [c70] [c68] [i30] [j86] [j84] [c64] [c62] [c61] [c58] [i21] [i17] [i15] [j74] [j73] [j70] [i12] [i9] [j64] [j63] [j62] [j58] [j57] [j54] [c50] [c49] [c48] [c47] [c46] [j51] [j50] [j49] [j48] [c44] [c42] [c41] [c39] [j44] [j43] [j41] [c38] [j40] [j39] [j36] [j33] [c31] [c29] [j31] [c21] [i2] [j18] [j14] [c5] [c4] [c2]
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