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Yang Shi 0003
Person information
- affiliation: Sun Yat-sen University, School of Information Science and Technology, Guangzhou, China
Other persons with the same name
- Yang Shi — disambiguation page
- Yang Shi 0001
— University of Victoria, Department of Mechanical Engineering, BC, Canada (and 2 more)
- Yang Shi 0002
- Yang Shi 0004
- Yang Shi 0005 — University of California, Irvine, CA, USA
- Yang Shi 0006
- Yang Shi 0007
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2020 – today
- 2024
- [j26]Yang Shi
A new recurrent neural network based on direct discretization method for solving discrete time-variant matrix inversion with application. Inf. Sci. 652: 119729 (2024) - [j25]Yang Shi
Neurodynamics for Equality-Constrained Time-Variant Nonlinear Optimization Using Discretization. IEEE Trans. Ind. Informatics 20(2): 2354-2364 (2024) - [j24]Yang Shi
Real-Time Tracking Control and Efficiency Analyses for Stewart Platform Based on Discrete-Time Recurrent Neural Network. IEEE Trans. Syst. Man Cybern. Syst. 54(8): 5099-5111 (2024) - [c6]Dimitrios Gerontitis, Panagiotis Tzekis, Yang Shi:
Solving Different Numerical Linear Algebra Problems with a New General Fast Neurodynamics. ICACI 2024: 30-35 - [c5]Ruicong Wang, Qiaowen Shi, Xijie Wang, Bo Peng, Wei Chong, Yang Shi:
A RNN for Solving Discrete-Form Time-Varying Matrix Inversion: From Model Design to Parameter Analysis. ICACI 2024: 190-196 - 2023
- [j23]Yang Shi
Direct derivation scheme of DT-RNN algorithm for discrete time-variant matrix pseudo-inversion with application to robotic manipulator. Appl. Soft Comput. 133: 109861 (2023) - [j22]Yang Shi
An advanced discrete-time RNN for handling discrete time-varying matrix inversion: Form model design to disturbance-suppression analysis. CAAI Trans. Intell. Technol. 8(3): 607-621 (2023) - [j21]Chao Jiang, Yixiang Zhang, Chao Mou, Bin Li, Xiaobing Sun, Yang Shi
A new ZNN model for finding discrete time-variant matrix square root: From model design to parameter analysis. J. Comput. Appl. Math. 431: 115260 (2023) - [j20]Yang Shi
Discrete generalized-Sylvester matrix equation solved by RNN with a novel direct discretization numerical method. Numer. Algorithms 93(3): 971-992 (2023) - [j19]Ratikanta Behera
An efficient zeroing neural network for solving time-varying nonlinear equations. Neural Comput. Appl. 35(24): 17537-17554 (2023) - [j18]Yang Shi
A direct discretization recurrent neurodynamics method for time-variant nonlinear optimization with redundant robot manipulators. Neural Networks 164: 428-438 (2023) - [j17]Yang Shi
Tracking Control of Cable-Driven Planar Robot Based on Discrete-Time Recurrent Neural Network With Immediate Discretization Method. IEEE Trans. Ind. Informatics 19(6): 7414-7423 (2023) - [j16]Mei Liu
High-Order Robust Discrete-Time Neural Dynamics for Time-Varying Multilinear Tensor Equation With $\mathcal {M}$-Tensor. IEEE Trans. Ind. Informatics 19(9): 9457-9467 (2023) - [j15]Yang Shi
Novel Discrete-Time Recurrent Neural Network for Robot Manipulator: A Direct Discretization Technical Route. IEEE Trans. Neural Networks Learn. Syst. 34(6): 2781-2790 (2023) - 2022
- [j14]Dimitrios Gerontitis, Ratikanta Behera, Yang Shi, Predrag S. Stanimirovic
A robust noise tolerant zeroing neural network for solving time-varying linear matrix equations. Neurocomputing 508: 254-274 (2022) - [j13]Yang Shi
Recurrent neural dynamics for handling linear equation system with rank-deficient coefficient and disturbance existence. J. Frankl. Inst. 359(7): 3090-3102 (2022) - [j12]Yimeng Qi
Robust k-WTA Network Generation, Analysis, and Applications to Multiagent Coordination. IEEE Trans. Cybern. 52(8): 8515-8527 (2022) - [j11]Yang Shi
Novel Discrete-Time Recurrent Neural Networks Handling Discrete-Form Time-Variant Multi-Augmented Sylvester Matrix Problems and Manipulator Application. IEEE Trans. Neural Networks Learn. Syst. 33(2): 587-599 (2022) - 2021
- [j10]Yang Shi, Chao Mou, Yimeng Qi, Bin Li, Shuai Li, Baoqing Yang:
Design, analysis and verification of recurrent neural dynamics for handling time-variant augmented Sylvester linear system. Neurocomputing 426: 274-284 (2021) - [j9]Jipeng Qiang
LSBert: Lexical Simplification Based on BERT. IEEE ACM Trans. Audio Speech Lang. Process. 29: 3064-3076 (2021) - [j8]Jian Li
Unified Model Solving Nine Types of Time-Varying Problems in the Frame of Zeroing Neural Network. IEEE Trans. Neural Networks Learn. Syst. 32(5): 1896-1905 (2021) - [c4]Yang Shi, Wenhan Zhao
Solving discrete time-varying complex division using recurrent neural network with disturbance suppression. ICAC 2021: 1-5 - 2020
- [j7]Yang Shi
Proposing, developing and verification of a novel discrete-time zeroing neural network for solving future augmented Sylvester matrix equation. J. Frankl. Inst. 357(6): 3636-3655 (2020) - [j6]Yang Shi
New Discrete-Time Models of Zeroing Neural Network Solving Systems of Time-Variant Linear and Nonlinear Inequalities. IEEE Trans. Syst. Man Cybern. Syst. 50(2): 565-576 (2020) - [i1]Jipeng Qiang, Xinyu Lu
Chinese Lexical Simplification. CoRR abs/2010.07048 (2020)
2010 – 2019
- 2019
- [j5]Zhangqiang Yin, Kang Liu, Yuanhang Chen, Rui Xue, Jian Li, Yang Shi
Performance Analyses of Four-Instant Discretization Formulas With Application to Generalized-Sylvester-Type Future Matrix Equation. IEEE Access 7: 152258-152266 (2019) - [j4]Yunong Zhang
General four-step discrete-time zeroing and derivative dynamics applied to time-varying nonlinear optimization. J. Comput. Appl. Math. 347: 314-329 (2019) - [j3]Yang Shi
Solving future equation systems using integral-type error function and using twice ZNN formula with disturbances suppressed. J. Frankl. Inst. 356(4): 2130-2152 (2019) - [c3]Liangjie Ming, Nini Shi, Yang Shi, Yunong Zhang
Future Linear Matrix Equation of Generalized Sylvester Type Solved by Zeroing Neural Dynamics and 5-Instant ZeaD Formula. ICNC-FSKD 2019: 260-270 - 2018
- [j2]Yang Shi, Yunong Zhang
Discrete time-variant nonlinear optimization and system solving via integral-type error function and twice ZND formula with noises suppressed. Soft Comput. 22(21): 7129-7141 (2018) - [j1]Yang Shi
Proposing and Validation of a New Four-Point Finite-Difference Formula With Manipulator Application. IEEE Trans. Ind. Informatics 14(4): 1323-1333 (2018) - [c2]Yunong Zhang
Any ZeaD Formula of Six Instants Having No Quartic or Higher Precision with Proof. ICSAI 2018: 705-709 - 2016
- [c1]Yunong Zhang
Numerical experiments and verifications of ZFD formula 4NgSFD for first-order derivative discretization and approximation. ICMLC 2016: 87-92
Coauthor Index
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