A5082042786- stochastic dynamics and bifurcation
- Probabilistic and Robust Engineering Design
- Diffusion and Search Dynamics
- Fractional Differential Equations Solutions
- Advanced Thermodynamics and Statistical Mechanics
- Ecosystem dynamics and resilience
- Nonlinear Dynamics and Pattern Formation
- Model Reduction and Neural Networks
- Statistical Mechanics and Entropy
- Magnetic confinement fusion research
- Fluid Dynamics and Turbulent Flows
- Cryospheric studies and observations
- Climate variability and models
- Micro and Nano Robotics
- Stochastic processes and statistical mechanics
- Land Use and Ecosystem Services
- Climate change and permafrost
- Atmospheric chemistry and aerosols
- Chaos control and synchronization
- Stochastic processes and financial applications
- Modular Robots and Swarm Intelligence
- Microfluidic and Bio-sensing Technologies
- Control Systems and Identification
- Neural dynamics and brain function
- Groundwater and Isotope Geochemistry
Northwestern Polytechnical University
2015-2025
Southwestern Institute of Physics
2008-2024
Chinese Academy of Sciences
2016-2023
Northwest Institute of Eco-Environment and Resources
2016-2023
University of Chinese Academy of Sciences
2019-2023
Huazhong University of Science and Technology
2019-2020
Potsdam Institute for Climate Impact Research
2016-2019
Humboldt-Universität zu Berlin
2017-2019
Shijiazhuang Tiedao University
2019
Shanxi University
2007
The probability density function of stochastic differential equations is governed by the Fokker-Planck (FP) equation. A novel machine learning method developed to solve general FP based on deep neural networks. proposed algorithm does not require any interpolation and coordinate transformation, which different from traditional numercial methods. main novelty this paper that penalty factors are introduced overcome local optimization for approach, corresponding setting rules given. Meanwhile,...
Building a virtual cell requires comprehensive understanding of protein network dynamics which necessitates large-scale perturbation proteome data and intelligent computational models learned from the corpus. Here, we generate dataset over 38 million perturbed measurements in breast cancer lines develop neural ordinary differential equation-based foundation model, namely ProteinTalks. During pretraining, ProteinTalks gains fundamental cellular dynamics. Our model encodes networks exhibits...
Abstract A bistable toggle switch is a paradigmatic model in the field of biology. The dynamics system induced by Gaussian noise has been intensively investigated, but cannot incorporate large bursts typically occurring real experiments. This paper aims to examine effects variations from one protein imposed non-Gaussian Lévy noise, which able describe even jumps, on coherent and on/off via steady-state probability density, joint density mean first passage time. We find that burst due noises...
Rough energy landscape and noisy environment are two common features in many subjects, such as protein folding. Due to the wide findings of bursting or spiking phenomenon biology science, small diffusions mixing large jumps adopted model that can be properly described by Lévy noise. We combine noise with rough landscape, modeled a potential function superimposed fast oscillating function, study transport particle triple-well excited noise, rather than only perturbations. The probabilities...
Abstract Since the last IAEA Fusion Energy Conference in 2018, significant progress of experimental program HL-2A has been achieved on developing advanced plasma physics, edge localized mode (ELM) control physics and technology. Optimization confinement performed. In particular, high- β N H-mode plasmas exhibiting an internal transport barrier have obtained (normalized pressure reached up to 3). Injection impurity improved confinement. ELM using resonance magnetic perturbation or injection a...
Ecosystem services in arid inland regions are significantly affected by climate change and land use/land cover associated with agricultural activity. However, the dynamics relationships of ecosystem natural anthropogenic drivers still less understood. In this study, spatiotemporal patterns Hexi Region were quantified based on multiple high-resolution datasets, InVEST model Revised Wind Erosion Equation (RWEQ) model. addition, trade-offs synergistic among also explored Pearson correlation...
Weak fault signals are often overwhelmed by strong noise or interference. The key issue in diagnosis is to accurately extract useful characteristics. Stochastic resonance an important signal processing method that utilizes enhance weak signals. In this paper, address the issues of output saturation and imperfect optimization potential structure models classical bistable stochastic (CBSR), we propose a piecewise asymmetric system. A two-state model used theoretically derive signal-to-noise...
Scaled Brownian motions (SBMs) with power-law time-dependent diffusivity have been used to describe various types of anomalous diffusion yet Gaussian observed in granular gases kinetics, turbulent diffusion, and molecules mobility cells, name a few. However, some these systems may exhibit non-Gaussian behavior which can be described by SBM diffusing (DD-SBM). Here, we numerically investigate both free confined DD-SBM models characterized fixed or stochastic scaling exponent diffusivity. The...
A system with fractional damping and a viscoelastic term subject to narrow-band noise is considered in this paper. Based on the revisit of Lindstedt–Poincaré (LP) multiple scales method, we present new procedure obtain second-order approximate analytical solution, then frequency–amplitude response equations deterministic case first- steady-state moments stochastic are derived theoretically. Numerical simulation applied verify effectiveness proposed which shows good agreement results....
In this paper, we consider the non-Lipschitz stochastic differential equations and functional with delays driven by Lévy noise, approximation theorems for solutions to these two kinds of will be proposed respectively. Non-Lipschitz condition is much weaker than Lipschitz one. The simplified defined make its converge that corresponding original both in sense mean square probability, which constitute theorems. Copyright © 2014 John Wiley & Sons, Ltd.
Abstract In this paper, we have investigated the collective dynamical behaviors of a network identical Hindmarsh–Rose neurons that are coupled under small-world schemes upon addition α -stable Lévy noise. According to firing patterns each neuron, distinguish neuronal into spike state, burst state and spike-burst coexistence neuron with both pattern pattern. Moreover, strength is proposed identify states system. Furthermore, an interesting phenomenon observed system presents coherence...