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Unsupervised Learning of 3-D Local Features From Raw Voxels Based on a Novel Permutation Voxelization Strategy Journal article
IEEE Transactions on Cybernetics, 2019,Volume: 49,Issue: 2,Page: 481-494
Authors:  Han Z.;  Liu Z.;  Han J.;  Vong C.-M.;  Bu S.;  Chen C.L.P.
Favorite |  | TC[WOS]:0 TC[Scopus]:16 | Submit date:2019/02/11
3-D local features  3-D voxelization  deep learning  stacked sparse autoencoder (SSAE)  unsupervised feature learning  
SeqViews2SeqLabels: Learning 3D global features via aggregating sequential views by RNN with attention Journal article
IEEE Transactions on Image Processing, 2019,Volume: 28,Issue: 2,Page: 658-672
Authors:  Han Z.;  Shang M.;  Liu Z.;  Vong C.-M.;  Liu Y.-S.;  Zwicker M.;  Han J.;  Chen C.L.P.
Favorite |  | TC[WOS]:40 TC[Scopus]:53 | Submit date:2019/02/14
3d Feature Learning  Attention  Rnn  Sequential Labels  Sequential Views  View Aggregation  
A Regularized Variable Projection Algorithm for Separable Nonlinear Least-Squares Problems Journal article
IEEE Transactions on Automatic Control, 2019,Volume: 64,Issue: 2,Page: 526-537
Authors:  Chen G.-Y.;  Gan M.;  Chen C.L.P.;  Li H.-X.
Favorite |  | TC[WOS]:82 TC[Scopus]:87 | Submit date:2019/02/11
Data fitting  regularization  separable nonlinear least squares (SNLLS)  variable projection (VP)  weighted generalized cross validation (WGCV)  
Fuzzy adaptive finite-time control design for nontriangular stochastic nonlinear systems Journal article
IEEE Transactions on Fuzzy Systems, 2019,Volume: 27,Issue: 1,Page: 172-184
Authors:  Sui S.;  Chen C.L.P.;  Tong S.
Favorite |  | TC[WOS]:84 TC[Scopus]:91 | Submit date:2019/02/11
Multiple-input and multiple-output (MIMO) stochastic nonlinear systems  nontriangular form  state filter  stochastically finite-time control  
Fuzzy adaptive compensation control of uncertain stochastic nonlinear systems with actuator failures and input hysteresis Journal article
IEEE Transactions on Cybernetics, 2019,Volume: 49,Issue: 1,Page: 2-13
Authors:  Wang J.;  Liu Z.;  Chen C.L.P.;  Zhang Y.
Favorite |  | TC[WOS]:26 TC[Scopus]:28 | Submit date:2019/02/11
Actuator failure/fault  adaptive control  hysteresis  stochastic nonlinear systems  transient performance  
Adaptive Reinforcement Learning Control Based on Neural Approximation for Nonlinear Discrete-Time Systems with Unknown Nonaffine Dead-Zone Input Journal article
IEEE Transactions on Neural Networks and Learning Systems, 2019,Volume: 30,Issue: 1,Page: 295-305
Authors:  Liu Y.-J.;  Li S.;  Tong S.;  Chen C.L.P.
Favorite |  | TC[WOS]:24 TC[Scopus]:27 | Submit date:2019/02/11
Discrete-time systems  neural networks (NNs)  nonlinear systems  optimal control  reinforcement learning  
Neural-dynamic optimization-based model predictive control for tracking and formation of nonholonomic multirobot systems Journal article
IEEE Transactions on Neural Networks and Learning Systems, 2018,Volume: 29,Issue: 12,Page: 6113-6122
Authors:  Li Z.;  Yuan W.;  Chen Y.;  Ke F.;  Chu X.;  Chen C.L.P.
Favorite |  | TC[WOS]:19 TC[Scopus]:26 | Submit date:2019/02/11
Formation control  multiple mobile robots  neural-dynamic optimization  nonlinear model predictive control (NMPC)  
Design of highly nonlinear substitution boxes based on I-Ching operators Journal article
IEEE Transactions on Cybernetics, 2018,Volume: 48,Issue: 12,Page: 3349-3358
Authors:  Zhang T.;  Chen C.L.P.;  Chen L.;  Xu X.;  Hu B.
Favorite |  | TC[WOS]:85 TC[Scopus]:101 | Submit date:2019/02/13
Boolean function  I-Ching  I-Ching operators (ICOs)  periodic iterated function (PIF)  substitution box (S-Box)  
Finite-time formation control of under-actuated ships using nonlinear sliding mode control Journal article
IEEE Transactions on Cybernetics, 2018,Volume: 48,Issue: 11,Page: 3243-3253
Authors:  Li T.;  Zhao R.;  Chen C.L.P.;  Fang L.;  Liu C.
Favorite |  | TC[WOS]:62 TC[Scopus]:76 | Submit date:2019/02/11
Finite-time stability  formation control  nonlinear sliding mode control  under-actuated ships  
Optimized Multi-Agent Formation Control Based on an Identifier-Actor-Critic Reinforcement Learning Algorithm Journal article
IEEE Transactions on Fuzzy Systems, 2018,Volume: 26,Issue: 5,Page: 2719-2731
Authors:  Wen G.;  Chen C.L.P.;  Feng J.;  Zhou N.
Favorite |  | TC[WOS]:23 TC[Scopus]:28 | Submit date:2019/02/11
Fuzzy logic systems (FLSs)  identifier-actor-critic architecture  multi-agent formation  optimized formation control  reinforcement learning (RL)