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Feature Aggregation With Reinforcement Learning for Video-Based Person Re-Identification 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 12, 页码: 3847-3852
作者:  Zhang, Wei;  He, Xuanyu;  Lu, Weizhi;  Qiao, Hong;  Li, Yibin
收藏  |  浏览/下载：301/0  |  提交时间：2020/03/30
Feature extraction  Task analysis  Cameras  Noise measurement  Learning systems  Reinforcement learning  Feature aggregation  reinforcement learning (RL)  sequential decision making  video-based person re-identification (re-id)  
A Greedy Assist-as-Needed Controller for Upper Limb Rehabilitation 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 11, 页码: 3433-3443
作者:  Luo, Lincong;  Peng, Liang;  Wang, Chen;  Hou, Zeng-Guang
收藏  |  浏览/下载：211/0  |  提交时间：2020/03/30
Medical treatment  Training  Task analysis  Robot sensing systems  Impedance  Trajectory  Assist as needed (AAN)  challenge level  Gaussian radial basis function (RBF) network  motor capability  rehabilitation robot  upper limb  
Neural Adaptive Event-Triggered Control for Nonlinear Uncertain Stochastic Systems With Unknown Hysteresis 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 11, 页码: 3300-3312
作者:  Wang, Jianhui;  Liu, Zhi;  Zhang, Yun;  Chen, C. L. Philip
收藏  |  浏览/下载：258/0  |  提交时间：2020/03/30
Actuators  Hysteresis  Nonlinear systems  Artificial neural networks  Adaptive systems  Stochastic systems  System performance  Actuator failure  adaptive control  event-triggered  neural networks (NNs)  stochastic nonlinear systems  unknown direction hysteresis  
Adaptive Neural State-Feedback Tracking Control of Stochastic Nonlinear Switched Systems: An Average Dwell-Time Method 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 4, 页码: 1076-1087
作者:  Niu, Ben;  Wang, Ding;  Alotaibi, Naif D.;  Alsaadi, Fuad E.
收藏  |  浏览/下载：234/0  |  提交时间：2019/12/16
Adaptive tracking control  average dwell time (ADT)  neural networks (NNs)  nonstrict-feedback structure  stochastic nonlinear systems  switched nonlinear systems  
Semantically Modeling of Object and Context for Categorization 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 4, 页码: 1013-1024
作者:  Zhang, Chunjie;  Cheng, Jian;  Tian, Qi
收藏  |  浏览/下载：292/0  |  提交时间：2019/12/16
Context modeling  object categorization  object modeling  semantic representation  
Neural Network Filtering Control Design for Nontriangular Structure Switched Nonlinear Systems in Finite Time 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 7, 页码: 2153-2162
作者:  Sui, Shuai;  Chen, C. L. Philip;  Tong, Shaocheng
收藏  |  浏览/下载：259/0  |  提交时间：2019/12/16
Common Lyapunov function  finite time  non-triangular structure  switched systems  
Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 8, 页码: 2310-2323
作者:  Du, Changde;  Du, Changying;  Huang, Lijie;  He, Huiguang
Adobe PDF(3773Kb)  |  收藏  |  浏览/下载：335/41  |  提交时间：2019/12/16
Deep neural network (DNN)  image reconstruction  multiview learning  neural decoding  variational Bayesian inference  
Modified Gram-Schmidt Method-Based Variable Projection Algorithm for Separable Nonlinear Models 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 8, 页码: 2410-2418
作者:  Chen, Guang-Yong;  Gan, Min;  Ding, Feng;  Chen, C. L. Philip
收藏  |  浏览/下载：238/0  |  提交时间：2019/12/16
Data fitting  modified Gram-Schmidt (MGS)  parameter estimation  separable nonlinear least-squares problem  variable projection (VP)  
Universal Approximation Capability of Broad Learning System and Its Structural Variations 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 4, 页码: 1191-1204
作者:  Chen, C. L. Philip;  Liu, Zhulin;  Feng, Shuang
收藏  |  浏览/下载：254/0  |  提交时间：2019/12/16
Broad learning system (BLS)  deep learning  face recognition  functional link neural networks (FLNNs)  non-linear function approximation  time-variant big data modeling  universal approximation  
Adaptive Reinforcement Learning Control Based on Neural Approximation for Nonlinear Discrete-Time Systems With Unknown Nonaffine Dead-Zone Input 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 卷号: 30, 期号: 1, 页码: 295-305
作者:  Liu, Yan-Jun;  Li, Shu;  Tong, Shaocheng;  Chen, C. L. Philip
收藏  |  浏览/下载：302/0  |  提交时间：2019/07/12
Discrete-time systems  neural networks (NNs)  nonlinear systems  optimal control  reinforcement learning