Yuming Wang

Beibei Li, Yutian Chi, Yuming Wang

This study introduces a novel approach that integrates the magnetic field data correction from the Tianwen-1 Mars mission with a neural network architecture constrained by physical principles derived from Maxwell's equation equations. By employing a Transformer based model capable of efficiently handling sequential data, the method corrects measurement anomalies caused by satellite dynamics, instrument interference, and environmental noise. As a result, it significantly improves both the accuracy and the physical consistency of the calibrated data. Compared to traditional methods that require long data segments and manual intervention often taking weeks or even months to complete this new approach can finish calibration in just minutes to hours, and predictions are made within seconds. This innovation not only accelerates the process of space weather modeling and planetary magnetospheric studies but also provides a robust framework for future planetary exploration and solar wind interaction research.

Xiaohu Ge, Xi Huang, Yuming Wang et al.

It is widely recognized that besides the quality of service (QoS), the energy efficiency is also a key parameter in designing and evaluating mobile multimedia communication systems, which has catalyzed great interest in recent literature. In this paper, an energy efficiency model is first proposed for multiple-input multiple-output orthogonal-frequency-division-multiplexing (MIMO-OFDM) mobile multimedia communication systems with statistical QoS constraints. Employing the channel matrix singular-value-decomposition (SVD) method, all subchannels are classified by their channel characteristics. Furthermore, the multi-channel joint optimization problem in conventional MIMO-OFDM communication systems is transformed into a multi-target single channel optimization problem by grouping all subchannels. Therefore, a closed-form solution of the energy efficiency optimization is derived for MIMO-OFDM mobile mlutimedia communication systems. As a consequence, an energy-efficiency optimized power allocation (EEOPA) algorithm is proposed to improve the energy efficiency of MIMO-OFDM mobile multimedia communication systems. Simulation comparisons validate that the proposed EEOPA algorithm can guarantee the required QoS with high energy efficiency in MIMO-OFDM mobile multimedia communication systems.