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Ying Tan
Ying Tan
Professor, University of Melbourne
Verified email at unimelb.edu.au
Title
Cited by
Cited by
Year
Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics
Y Wang, S Zhang, F Li, Y Zhou, Y Zhang, Z Wang, R Zhang, J Zhu, Y Ren, ...
Nucleic acids research 48 (D1), D1031-D1041, 2020
8592020
On non-local stability properties of extremum seeking control
Y Tan, D Nešić, I Mareels
Automatica 42 (6), 889-903, 2006
6902006
Linear and nonlinear iterative learning control
JX Xu, Y Tan
Springer, 2003
6852003
Extremum seeking from 1922 to 2010
Y Tan, WH Moase, C Manzie, D Nešić, IMY Mareels
Proceedings of the 29th Chinese control conference, 14-26, 2010
5712010
A composite energy function-based learning control approach for nonlinear systems with time-varying parametric uncertainties
JX Xu, Y Tan
IEEE Transactions on Automatic Control 47 (11), 1940-1945, 2002
2802002
On global extremum seeking in the presence of local extrema
Y Tan, D Nešić, IMY Mareels, A Astolfi
Automatica 45 (1), 245-251, 2009
2602009
NPASS: natural product activity and species source database for natural product research, discovery and tool development
X Zeng, P Zhang, W He, C Qin, S Chen, L Tao, Y Wang, Y Tan, D Gao, ...
Nucleic acids research 46 (D1), D1217-D1222, 2018
2322018
Iterative learning control with mixed constraints for point-to-point tracking
CT Freeman, Y Tan
IEEE Transactions on Control Systems Technology 21 (3), 604-616, 2012
1942012
On the choice of dither in extremum seeking systems: A case study
Y Tan, D Nešić, I Mareels
Automatica 44 (5), 1446-1450, 2008
1912008
A unifying approach to extremum seeking: Adaptive schemes based on estimation of derivatives
D Nesić, Y Tan, WH Moase, C Manzie
49th IEEE conference on decision and control (CDC), 4625-4630, 2010
1882010
Iterative learning control design based on composite energy function with input saturation
JX Xu, Y Tan, TH Lee
Automatica 40 (8), 1371-1377, 2004
1872004
Robust optimal design and convergence properties analysis of iterative learning control approaches
JX Xu, Y Tan
Automatica 38 (11), 1867-1880, 2002
1542002
A practical 3D-printed soft robotic prosthetic hand with multi-articulating capabilities
A Mohammadi, J Lavranos, H Zhou, R Mutlu, G Alici, Y Tan, P Choong, ...
PloS one 15 (5), e0232766, 2020
1402020
Optimal iterative learning control design for multi-agent systems consensus tracking
S Yang, JX Xu, D Huang, Y Tan
Systems & Control Letters 69, 80-89, 2014
1222014
Unified frameworks for sampled-data extremum seeking control: Global optimisation and multi-unit systems
SZ Khong, D Nešić, Y Tan, C Manzie
Automatica 49 (9), 2720-2733, 2013
1222013
Distributed deception attack detection in platoon-based connected vehicle systems
Z Ju, H Zhang, Y Tan
IEEE transactions on vehicular technology 69 (5), 4609-4620, 2020
1182020
NEAT1 regulates neuroglial cell mediating Aβ clearance via the epigenetic regulation of endocytosis-related genes expression
Z Wang, Y Zhao, N Xu, S Zhang, S Wang, Y Mao, Y Zhu, B Li, Y Jiang, ...
Cellular and Molecular Life Sciences 76, 3005-3018, 2019
1102019
Host cell transcriptome profile during wild-type and attenuated dengue virus infection
OM Sessions, Y Tan, KC Goh, Y Liu, P Tan, S Rozen, EE Ooi
PLoS neglected tropical diseases 7 (3), e2107, 2013
972013
Improved prediction of aqueous solubility of novel compounds by going deeper with deep learning
Q Cui, S Lu, B Ni, X Zeng, Y Tan, YD Chen, H Zhao
Frontiers in oncology 10, 121, 2020
942020
Deception attack detection and estimation for a local vehicle in vehicle platooning based on a modified UFIR estimator
Z Ju, H Zhang, Y Tan
IEEE Internet of Things Journal 7 (5), 3693-3705, 2020
912020
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