Method for estimating non-measurable parameters of gas turbine engines considering variations in technical condition by Sergiy Yepifanov, Oleksii Bondarenko

“…To achieve this, matrix algebra methods are employed, including pseudoinverse matrices, singular value decomposition (SVD), and weighted least squares (WLS). …”
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Bistatic ISAR Sparse Imaging Method for High-Speed Moving Target Based on Dechirping Processing by Chuangzhan Zeng, Weigang Zhu, Xin Jia

“…At first, based on the motion decomposition idea, the B-ISAR echo model of the high-speed moving target is established. …”
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A Three-Dimensional Coverage Path Planning Method for Robots for Farmland with Complex Hilly Terrain by Hanbing Jiang, Ping Yang

“…In this paper, for the full-coverage path-planning problem of hilly terrain farmland, based on analyzing the terrain characteristics of hilly farmland and the energy consumption model of robots traveling on non-flat ground, we propose a region decomposition method oriented to special terrain and prioritize the coverage of special terrain areas. …”
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Wake vortex evolution analysis of trapezoidal wings with varied flap configurations based on the Liutex method by Jinyan Cai, Dong Li, Qiang Li, Jiaolin Cui, Ziming Xu, Gang Wang, Dawei Liu

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Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection by Daihong Jiang, Zhixiang Chen, Sanyou Zhang, Yunfei Li, Lu Zhao

“…Traditional low-rank decomposition methods aim to recover low-rank components and isolate sparse elements, but the structural integrity of the sparse components is often compromised. …”
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WCMU-net: An Effective Method for Reducing the Impact of Speckle Noise in SAR Image Change Detection by Yu Duan, Kaimin Sun, Wangbin Li, Jinjiang Wei, Song Gao, Yingjiao Tan, Wanghui Zhou, Jun Liu, Junyi Liu

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Reduced order modeling of blood perfusion in parametric multipatch liver lobules by Ahsan Ali Siddiqui, Etienne Jessen, Stein K. F. Stoter, David Néron, Dominik Schillinger

“…We then construct a reduced order model via proper orthogonal decomposition (POD). …”
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Fault Diagnosis Method of Permanent Magnet Synchronous Motor Demagnetization and Eccentricity Based on Branch Current by Zhiqiang Wang, Shangru Shi, Xin Gu, Zhezhun Xu, Huimin Wang, Zhen Zhang

“…Finally, to further improve diagnostic accuracy, a cascaded convolutional neural network based on dilated convolutional layers and multi-scale convolutional layers is designed as the diagnostic model. Experimental results show that the method proposed in this paper achieves a diagnostic accuracy of 98.6%, with a misjudgment rate of only about 2% and no overlapping feature results. …”
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Semi-Supervised Fault Diagnosis Method for Hydraulic Pumps Based on Data Augmentation Consistency Regularization by Siyuan Liu, Jixiong Yin, Zhengming Zhang, Yongqiang Zhang, Chao Ai, Wanlu Jiang

“…Due to the scarcity of labeled samples, the practical engineering application of deep learning-based hydraulic pump fault diagnosis methods is extremely challenging. This study proposes a semi-supervised learning method based on data augmented consistency regularization (DACR) to address the issue of lack of labeled data in diagnostic models. …”
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Multi-Level Decomposition and Interpretability-Enhanced Air Conditioning Load Forecasting Study by Xinting Yang, Ling Zhang, Hong Zhao, Wenhua Zhang, Chuan Long, Gang Wu, Junhao Zhao, Xiaodong Shen

“…Results show that the proposed method significantly outperforms the LSTM model without decomposition and other benchmark models in prediction accuracy, with the Root Mean Square Error (RMSE) reductions ranging from 40.26% to 74.18% and the Modified Mean Absolute Percentage Error (MMAPE) reductions from 37.75% to 73.41%. …”
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Coupled estimation of internal tides and turbulent motions via statistical modal decomposition by I. Maingonnat, G. Tissot, N. Lahaye

“…The method is presented and tested in an idealised framework based on the rotating-shallow-water model, where we provide a physical interpretation for the decomposition method based on theoretical considerations. …”
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Epileptic Seizure Detection in Neonatal EEG Using a Multi-Band Graph Neural Network Model by Lihan Tang, Menglian Zhao

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Complete Mode Spectrum Decomposition of Complex‐Structured Light by Computer‐Generated Holography by Yunfei Ma, Zilong Zhang, Yuqi Wang, Hongzhi Yang, Wei He, Lingyu Kong, Suyi Zhao, Xiaotian Li, Yetong Hu, Changming Zhao

“…Analyzing or probing a complex‐structured light field with a simple model to obtain its mode composition sequence and phase delays among eigenmodes is challenging. …”
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Research on Bearing Fault Diagnosis Method for Varying Operating Conditions Based on Spatiotemporal Feature Fusion by Jin Wang, Yan Wang, Junhui Yu, Qingping Li, Hailin Wang, Xinzhi Zhou

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Transformer-Based Decomposition of Electrodermal Activity for Real-World Mental Health Applications by Charalampos Tsirmpas, Stasinos Konstantopoulos, Dimitris Andrikopoulos, Konstantina Kyriakouli, Panagiotis Fatouros

“…The model leverages pooling and trend-removal mechanisms to enforce physiologically meaningful decompositions. …”
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A novel interval prediction method in wind speed based on deep learning and combination prediction by XueJun Chen, Tao Han, Peng Cheng, Xuanfang Da

“…Abstract The combined method for interval forecasting (CMIF) is proposed for improved real-time prediction of wind speed uncertainty to facilitate wind turbine operation and power grid dispatching. …”
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Fast Adaptive Sparse Iterative Reweighted Super-Resolution Method for Forward-Looking Radar Imaging by Jiawei Luo, Yulin Huang, Ruitao Li, Deqing Mao, Yongchao Zhang, Yin Zhang, Jianyu Yang

“…First, we establish the super-resolution model of forward-looking radar and analyze the user parameter selection problem in the conventional <inline-formula><tex-math notation="LaTeX">$L_{1}$</tex-math></inline-formula>-IRN method. …”
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Advances and applications of empirical mode decomposition and its variants in hydrology: A review by CHEN Yunfei, LIU Zuyu, LIU Xiuhua, HE Junqi, ZHENG Ce, MA Yandong

“…We provide a comprehensive overview of the fundamental theory, methodological characteristics, and current challenges of EMD, covering five EMD-based methods: Hilbert-Huang Transform (HHT), Ensemble Empirical Mode Decomposition (EEMD), Multivariate Empirical Mode Decomposition (MEMD), Extreme Point Symmetric Mode Decomposition (ESMD), and Variational Mode Decomposition (VMD). …”
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Offline reinforcement learning combining generalized advantage estimation and modality decomposition interaction by Kaixin Jin, Lifang Wang, Xiwen Wang, Wei Guo, Qiang Han, Xiaoqing Yu

“…Abstract Transformers show great potential in offline reinforcement learning via trajectory sequence modeling for action prediction. However, existing Transformer-based methods face limitations, such as ineffective trajectory stitching and the neglect of deep interactions within and between multimodal information in trajectories. …”
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Dynamic identification method for flow patterns of liquid-solid two-phase flow in horizontal pipelines by ZHUJUNLIANG Junliang, ZHAOZHIFENG, WANGSHUGANG, JIANG Shuang

“…Compared with experimental and numerical simulation methods, the identification method of liquid-solid two-phase flow patterns based on DMD has significant advantages in data processing, accuracy, efficiency, and applicability. …”
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