| Global anti-synchronization of complex-valued memristive neural networks with time delays D Liu, S Zhu, K Sun IEEE transactions on cybernetics 49 (5), 1735-1747, 2018 | 121 | 2018 |
| Finite-time stability of delayed memristor-based fractional-order neural networks C Chen, S Zhu, Y Wei IEEE transactions on cybernetics 50 (4), 1607-1616, 2018 | 106 | 2018 |
| Synchronization of memristive complex-valued neural networks with time delays via pinning control method S Zhu, D Liu, C Yang, J Fu IEEE Transactions on Cybernetics 50 (8), 3806-3815, 2019 | 88 | 2019 |
| Exponential passivity of neural networks with time-varying delay and uncertainty S Zhu, Y Shen, G Chen Physics Letters A 375 (2), 136-142, 2010 | 84 | 2010 |
| Hybrid parallel stochastic configuration networks for industrial data analytics W Dai, X Zhou, D Li, S Zhu, X Wang IEEE Transactions on Industrial Informatics 18 (4), 2331-2341, 2021 | 55 | 2021 |
| Leakage delay-dependent stability analysis for complex-valued neural networks with discrete and distributed time-varying delays R Samidurai, R Sriraman, S Zhu Neurocomputing 338, 262-273, 2019 | 53 | 2019 |
| Synchronization stability of memristor-based complex-valued neural networks with time delays D Liu, S Zhu, E Ye Neural Networks 96, 115-127, 2017 | 53 | 2017 |
| Passivity analysis of stochastic delayed neural networks with Markovian switching S Zhu, Y Shen Neurocomputing 74 (10), 1754-1761, 2011 | 49 | 2011 |
| Global Mittag–Leffler stabilization of fractional-order complex-valued memristive neural networks W Chang, S Zhu, J Li, K Sun Applied Mathematics and Computation 338, 346-362, 2018 | 46 | 2018 |
| Fast and reproducible ELISA laser platform for ultrasensitive protein quantification X Tan, Q Chen, H Zhu, S Zhu, Y Gong, X Wu, YC Chen, X Li, MWH Li, ... ACS sensors 5 (1), 110-117, 2019 | 36 | 2019 |
| Anti-synchronization of complex-valued memristor-based delayed neural networks D Liu, S Zhu, K Sun Neural Networks 105, 1-13, 2018 | 36 | 2018 |
| Two algebraic criteria for input-to-state stability of recurrent neural networks with time-varying delays S Zhu, Y Shen Neural Computing and Applications 22, 1163-1169, 2013 | 34 | 2013 |
| Robustness analysis for connection weight matrices of global exponential stability of stochastic recurrent neural networks S Zhu, Y Shen Neural Networks 38, 17-22, 2013 | 33 | 2013 |
| Noise further expresses exponential decay for globally exponentially stable time-varying delayed neural networks S Zhu, Q Yang, Y Shen Neural Networks 77, 7-13, 2016 | 31 | 2016 |
| Multistability of dynamic memristor delayed cellular neural networks with application to associative memories K Deng, S Zhu, G Bao, J Fu, Z Zeng IEEE Transactions on Neural Networks and Learning Systems 34 (2), 690-702, 2021 | 30 | 2021 |
| Tunable Brillouin and Raman microlasers using hybrid microbottle resonators S Zhu, B Xiao, B Jiang, L Shi, X Zhang Nanophotonics 8 (5), 931-940, 2019 | 30 | 2019 |
| Mean square exponential input-to-state stability of stochastic memristive complex-valued neural networks with time varying delay D Liu, S Zhu, W Chang International Journal of Systems Science 48 (9), 1966-1977, 2017 | 30 | 2017 |
| New criteria on stability of dynamic memristor delayed cellular neural networks K Deng, S Zhu, W Dai, C Yang, S Wen IEEE Transactions on Cybernetics 52 (6), 5367-5379, 2020 | 29 | 2020 |
| Input-to-state stability of memristor-based complex-valued neural networks with time delays D Liu, S Zhu, W Chang Neurocomputing 221, 159-167, 2017 | 27 | 2017 |
| PID control for output synchronization of multiple output coupled complex networks L Zhao, S Wen, M Xu, K Shi, S Zhu, T Huang IEEE Transactions on Network Science and Engineering 9 (3), 1553-1566, 2022 | 26 | 2022 |
