A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng +4 more
wiley +1 more source
Nonlinear Stochastic Dynamics of the Intermediate Dispersive Velocity Equation with Soliton Stability and Chaos. [PDF]
Wali S +4 more
europepmc +1 more source
Characteristics comparative of gut microbiota in four small mammal species co-occurring in the Hengduan Mountains: differences in environmental adaptation strategies between alien and endemic species. [PDF]
Ma Y, Jia T, Zhu W, Fan L.
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Adaptive distributed stochastic deep reinforcement learning control for voltage and frequency restoration in islanded AC microgrids with communication noise and delay. [PDF]
Dehkordi NM, Nekoukar V.
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Robust Model Predictive Control with a Dynamic Look-Ahead Re-Entry Strategy for Trajectory Tracking of Differential-Drive Robots. [PDF]
Guffanti D +7 more
europepmc +1 more source
Square integrable solutions and stability of a second-order stochastic integro-differential equation. [PDF]
Oudjedi-Damerdji LF +4 more
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A perturbation-recovery generative autoencoder for heterogeneous graphs with attributes missing. [PDF]
Wang Q, Shao X, Huang X.
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AbstractDisturbance observer‐based elegant anti‐disturbance control (DOBEADC) scheme is proposed for a class of stochastic systems with nonlinear dynamics and multiple disturbances. The stochastic disturbance observer based on pole placement is constructed to estimate disturbance which is generated by an exogenous system.
Xinjiang Wei
exaly +3 more sources

