Yong Li

Correction: Development and validation of an explainable machine learning model for predicting the risk of sleep disorders in older adults with multimorbidity: a cross-sectional study

Xia Wang, Dan Zhang, Lu Liu, Yong Li et autres

Incorrect affiliation In the published article, there was an error in affiliation [one]. Instead of "[Dan Zhang2† 2Nursing Department, The People's Hospital of Wenjiang Chengdu, Chengdu, China]", it should be "[Dan Zhang2† 2Rehabilitation Department, Sichuan Provincial People's Hospital East Sichuan Hospital &Dazhou …

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Cross-Domain Complementary Dual-Stream Deep Self-Supervised Learning Framework for Human Activity Recognition on Wearable Devices

Yuang Chen, Yong Li, Shuai Lv, Fang Lin

Development and validation of an explainable machine learning model for predicting the risk of sleep disorders in older adults with multimorbidity: a cross-sectional study

Xia Wang, Dan Zhang, Lu Liu, Yong Li et autres

Objective: To develop and validate an explainable machine learning model for predicting the risk of sleep disorders in older adults with multimorbidity. Methods: A total of 471 older adults with multimorbidity were recruited between October and November 2024. We employed six machine …

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A Deep Learning-Based Method for Detection of Multiple Maneuvering Targets and Parameter Estimation

Beiming Yan, Yong Li, Qianlan Kou, Chen Ren et autres

With the rapid development of drone technology, target detection and estimation of radar parameters for maneuvering targets have become crucial. Drones, with their small radar cross-sections and high maneuverability, cause range migration (RM) and Doppler frequency migration (DFM), which complicate the use …

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Complex Convolution-Enhanced ADMM-Net for High-Resolution DOA Estimation with Sparse Linear Arrays

Beiming Yan, Yong Li, Wei Cheng, Limeng Dong et autres

This paper presents a high-resolution direction of arrival (DOA) estimation method for Sparse Linear Arrays (SLAs). Our approach innovatively integrates a complex convolutional neural network (Complex CNN) with an alternating direction method of multipliers network (ADMM-Net) framework to markedly improve DOA estimation …

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Adversarial Sample Generation Method for Modulated Signals Based on Edge-Linear Combination

Tianyi Wei, Yong Li, Yingtao Niu

In complex electromagnetic environments, wireless communication system reliability can be compromised by various types of jamming. To address the issue of jammers using deep neural network models to identify communication signal modulation method and apply targeted interference, this paper proposes a method …

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An improved adaptive CFAR detector for non-homogeneous environment

Xuan Du, Yong Li, Wei Cheng

The conventional variability index constant false alarm rate (VI-CFAR) algorithm experiences significant degradation in detection performance when interference targets are located on both sides of the reference window. To mitigate this challenge, this paper proposes an enhanced VITM-CFAR algorithm which integrates the …

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High-resolution multicomponent LFM parameter estimation based on deep learning

Beiming Yan, Yong Li, Wei Cheng, Limeng Dong et autres

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Research on risk prediction of tree growth in power transmission lines based on laser lidar

Shan Wu, Yong Li, Qi Liu, Rong Yu et autres

Responding to the increasing demand for intelligent power inspection management, the integration of various advanced technologies into the field of transmission line inspection and the efficient solution to the problem of tree obstacle growth has gradually become a cutting-edge direction. The growth …

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Research on Emotion Prediction Based on Emotional Changes in Dialogue Scenarios

Yong Li, Haixiao Zhang, Wendong Xu

In recent years, the application of emotional analysis in dialogues in human-computer interaction has received increasing attention. The main difference between emotional analysis in dialogues and emotional analysis in single sentences is the contextual information that influences the emotional tone in dialogues. …

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Data-Segmentation Verification and a Target Generative Adversarial Network: EEG-Based Emotion Recognition

Lufeng Yin, Yong Li

Emotion recognition is a crucial component of artificial intelligence. As one of the main factors in emotion recognition, data-driven affective computing heavily relies on high-quality training data, which may not always be readily available due to various reasons. Addressing the challenge of …

Adaptive Whitening and Feature Gradient Smoothing-Based Anti-Sample Attack Method for Modulated Signals in Frequency-Hopping Communication

Yanhan Zhu, Yong Li, Zhu Duan

In modern warfare, frequency-hopping communication serves as the primary method for battlefield information transmission, with its significance continuously growing. Fighting for the control of electromagnetic power on the battlefield has become an important factor affecting the outcome of war. As communication electronic …

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