Publication

Publications

1. P. Ernst, X. Ma, M. H. Nazari, H. Qian, L. Y. Wang, and G. Yin, Numerical solutions of a class of optimal stopping problems, Nonlinear Analysis: Hybrid Systems, 53 (2024): 101507.

2. H. Qian, F. Wu, and G. Yin,A class of numerical algorithms for stochastic differential equations with randomly varying truncations inspired by a stochastic optimization problem, accepted by Discrete Contin. Dyn. Syst. Ser. S.

3. H. Qian, G. Yin, and Q. Zhang, Deep Filtering with Adaptive Learning Rates, IEEE. Trans. Automat. Contr., 68 (2023), 3285-3299.

4. H. Qian and G. Yin, Moderate Deviations for the Langevin Equations: Strong Damping and Fast Markovian Switching, J. Math. Phys., 63 (2022), 123304, 28 pp.

5. H. Qian, Q. Zhang and G. Yin, Filtering with degenerate observation noise: A stochastic approximation approach, Automatica. 142 (2022): 110376, 9 pp.

6. H. Qian, Z. Wen, and G. Yin, Numerical Solutions for Optimal Control of Stochastic Kolmogorov Systems with Regime-Switching and Random Jumps,Stat. Inference Stoch. Process., 25 (2022): 105-125 (invited paper dedicated to the 90th birthday of Professor Rafail Khasminskii).

7. G. Yin, Z. Wen, H. Qian,and H. Nguyen, Numerical Solutions for Optimal Control of Stochastic Kolmogorov Systems, J. Syst. Sci. Complex., 34 (2021), 1703-1722.

Conference paper

1. X. Ma, H. Qian, L. Y. Wang, M. H. Nazari, and G. Yin, Numerical solutions for detecting contingency in modern power systems, 4th Information Communication Technologies Conference (ICTC), 2023, 390-395.

News article

1. H. Qian, G. Yin and Q. Zhang, A new computational method for nonlinear filtering, SIAM News, 56(5), 2023, page 1.

Preprints

1. H. Qian, Y. Cao, and G. Yin, Large Deviation Estimates for Nonlinear Filtering with Discontinuity and Small Noise.

2. H. Qian, Moderate Deviation Principles for Stochastic Differential Equations in a Fast Markovian Environment.