Advanced Science, EarlyView.Here, we demonstrate and investigate polarization‐enabled electromechanical responses in cryogenic physical vapor deposition (cryogenic PVD)‐deposited TexSe1‐x thin films, a tellurium‐based compound with a tunable bandgap and enhanced non‐centrosymmetry.
Chia‐Chen Chung +16 more
wiley +1 more source
Calibration Method for Relativistic Navigation System Using Parallel Q-Learning Extended Kalman Filter. [PDF]
Sensors (Basel)Xiong K, Zhao Q, Yuan L.
europepmc +1 more source
Temporal Interference Stimulation Enhances Neural Regeneration
Advanced Science, EarlyView.Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti +15 more
wiley +1 more source
Energy-Efficient Cooperative Transmission in Ultra-Dense Millimeter-Wave Network: Multi-Agent Q-Learning Approach. [PDF]
Sensors (Basel)Kim SY, Ko H.
europepmc +1 more source
Q-learning improved golden jackal optimization algorithm and its application to reliability optimization of hydraulic system. [PDF]
Sci RepChen D, Wang H, Hu D, Xian Q, Wu B.
europepmc +1 more source
Q-RPL: Q-Learning-Based Routing Protocol for Advanced Metering Infrastructure in Smart Grids. [PDF]
Sensors (Basel)Duenas Santos CL +5 more
europepmc +1 more source
Energy efficient group priority MAC protocol using hybrid Q-learning honey Badger Algorithm (QL-HBA) for IoT Networks. [PDF]
Sci RepVenkatachalam I +4 more
europepmc +1 more source
Enhancing the Efficiency of a Cybersecurity Operations Center Using Biomimetic Algorithms Empowered by Deep Q-Learning. [PDF]
Biomimetics (Basel)Olivares R +4 more
europepmc +1 more source
A Temporal Deep Q Learning for Optimal Load Balancing in Software-Defined Networks. [PDF]
Sensors (Basel)Sharma A +2 more
europepmc +1 more source
Related searches:
It is well known that the extension of Watkins' algorithm to general function approximation settings is challenging: does the “projected Bellman equation” have a solution? If so, is the solution useful in the sense of generating a good policy? And, if the preceding questions are answered in the affirmative, is the algorithm consistent?
Fan Lu +3 more
openaire +1 more source