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Zhou Fang
Zhou Fang
Postdoc, Department of Biosystems Science and Engineering, ETH Zurich
Verified email at bsse.ethz.ch - Homepage
Title
Cited by
Cited by
Year
Stabilization of input-disturbed stochastic port-Hamiltonian systems via passivity
Z Fang, C Gao
IEEE Transactions on Automatic Control 62 (8), 4159-4166, 2017
202017
Lyapunov Function Partial Differential Equations for Chemical Reaction Networks: Some Special Cases
Z Fang, C Gao
SIAM Journal on Applied Dynamical Systems 18 (2), 1163-1199, 2019
162019
Stochastic filtering for multiscale stochastic reaction networks based on hybrid approximations
Z Fang, A Gupta, M Khammash
Journal of Computational Physics 467, 111441, 2022
92022
Stochastic filters based on hybrid approximations of multiscale stochastic reaction networks
Z Fang, A Gupta, M Khammash
2020 59th IEEE Conference on Decision and Control (CDC), 4616-4621, 2020
82020
Convergence of regularized particle filters for stochastic reaction networks
Z Fang, A Gupta, M Khammash
SIAM Journal on Numerical Analysis 61 (2), 399-430, 2023
72023
Noise-to-state exponentially stabilizing (state, input)-disturbed CSTRs with non-vanishing noise
Y Lu, Z Fang, C Gao, D Dochain
Automatica 142, 110387, 2022
7*2022
Complex Balancing Reconstructed to the Asymptotic Stability of Mass-Action Chemical Reaction Networks with Conservation Laws
M Ke, Z Fang, C Gao
SIAM Journal on Applied Mathematics 79 (1), 55-74, 2019
72019
Stochastic weak passivity for weakly stabilizing stochastic systems with nonvanishing noise
Z Fang, C Gao, D Dochain
Systems & Control Letters, 2023
4*2023
Time-domain Boundedness of Noise-to-State Exponentially Stable Systems
Z Fang, C Gao
ESAIM: Control, Optimisation and Calculus of Variations 26 (4), 105, 23pp, 2020
4*2020
A divide-and-conquer method for analyzing high-dimensional noisy gene expression networks
Z Fang, A Gupta, S Kumar, M Khammash
bioRxiv, 2022.10. 28.514278, 2022
3*2022
Efficacy of Regularized Multitask Learning Based on SVM Models
S Chen, Z Fang, S Lu, C Gao
IEEE Transactions on Cybernetics, 2022
32022
Filtered finite state projection method for the analysis and estimation of stochastic biochemical reaction networks
ES D'Ambrosio, Z Fang, A Gupta, M Khammash
bioRxiv, 2022.10. 18.512737, 2022
32022
Adaptation mechanisms in phosphorylation cycles by allosteric binding and gene autoregulation
Z Fang, B Jayawardhana, AV der Schaft, C Gao
IEEE Transactions on Automatic Control, 2019
32019
On the relation between ω-limit set and boundaries of mass-action chemical reaction networks
X Zhang, Z Fang, C Gao, D Dochain
Automatica 149, 110828, 2023
22023
Thermodynamic Potentials from Stationary Probabilities
Z Fang, BE Ydstie, C Gao
IFAC-PapersOnLine 52 (7), 96-102, 2019
22019
Revisiting persistence of chemical reaction networks through lyapunov function partial differential equations
X Zhang, Z Fang, C Gao
arXiv preprint arXiv:1810.00225, 2018
22018
Integral regulation mechanism in phosphorylation cycles
Z Fang, B Jayawardhana, A van der Schaft, C Gao
2017 IEEE 56th Annual Conference on Decision and Control (CDC), 5322-5327, 2017
12017
Effective filtering approach for joint parameter-state estimation in SDEs via Rao-Blackwellization and modularization
Z Fang, A Gupta, M Khammash
arXiv preprint arXiv:2311.00836, 2023
2023
A Graphic Formulation of Nonisothermal Chemical Reaction Systems and the Analysis of Detailed Balanced Networks
Z Fang, A van der Schaft, C Gao
SIAM Journal on Applied Dynamical Systems 19 (4), 2594-2627, 2020
2020
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Articles 1–19