EURASIP Journal on Advances in Signal Processing最新文献_第3页

Enhancing human behavior recognition with spatiotemporal graph convolutional neural networks and skeleton sequences 利用时空图卷积神经网络和骨架序列增强人类行为识别能力

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-05-07 DOI: 10.1186/s13634-024-01156-w

Jianmin Xu, Fenglin Liu, Qinghui Wang, Ruirui Zou, Ying Wang, Junling Zheng, Shaoyi Du, Wei Zeng

{"title":"Enhancing human behavior recognition with spatiotemporal graph convolutional neural networks and skeleton sequences","authors":"Jianmin Xu, Fenglin Liu, Qinghui Wang, Ruirui Zou, Ying Wang, Junling Zheng, Shaoyi Du, Wei Zeng","doi":"10.1186/s13634-024-01156-w","DOIUrl":"https://doi.org/10.1186/s13634-024-01156-w","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Objectives</h3><p>This study aims to enhance supervised human activity recognition based on spatiotemporal graph convolutional neural networks by addressing two key challenges: (1) extracting local spatial feature information from implicit joint connections that is unobtainable through standard graph convolutions on natural joint connections alone. (2) Capturing long-range temporal dependencies that extend beyond the limited temporal receptive fields of conventional temporal convolutions.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>To achieve these objectives, we propose three novel modules integrated into the spatiotemporal graph convolutional framework: (1) a connectivity feature extraction module that employs attention to model implicit joint connections and extract their local spatial features. (2) A long-range frame difference feature extraction module that captures extensive temporal context by considering larger frame intervals. (3) A coordinate transformation module that enhances spatial representation by fusing Cartesian and spherical coordinate systems.</p><h3 data-test=\"abstract-sub-heading\">Findings</h3><p>Evaluation across multiple datasets demonstrates that the proposed method achieves significant improvements over baseline networks, with the highest accuracy gains of 2.76<span>(%)</span> on the NTU-RGB+D 60 dataset (Cross-subject), 4.1<span>(%)</span> on NTU-RGB+D 120 (Cross-subject), and 4.3<span>(%)</span> on Kinetics (Top-1), outperforming current state-of-the-art algorithms. This paper delves into the realm of behavior recognition technology, a cornerstone of autonomous systems, and presents a novel approach that enhances the accuracy and precision of human activity recognition.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"16 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on heart and lung sound separation method based on DAE–NMF–VMD 基于 DAE-NMF-VMD 的心肺声音分离方法研究

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-05-06 DOI: 10.1186/s13634-024-01152-0

Wenhui Sun, Yipeng Zhang, Fuming Chen

{"title":"Research on heart and lung sound separation method based on DAE–NMF–VMD","authors":"Wenhui Sun, Yipeng Zhang, Fuming Chen","doi":"10.1186/s13634-024-01152-0","DOIUrl":"https://doi.org/10.1186/s13634-024-01152-0","url":null,"abstract":"<p>Auscultation is the most effective method for diagnosing cardiovascular and respiratory diseases. However, stethoscopes typically capture mixed signals of heart and lung sounds, which can affect the auscultation effect of doctors. Therefore, the efficient separation of mixed heart and lung sound signals plays a crucial role in improving the diagnosis of cardiovascular and respiratory diseases. In this paper, we propose a blind source separation method for heart and lung sounds based on deep autoencoder (DAE), nonnegative matrix factorization (NMF) and variational mode decomposition (VMD). Firstly, DAE is employed to extract highly informative features from the heart and lung sound signals. Subsequently, NMF clustering is applied to group the heart and lung sounds based on their distinct periodicities, achieving the separation of the mixed heart and lung sounds. Finally, variational mode decomposition is used for denoising the separated signals. Experimental results demonstrate that the proposed method effectively separates heart and lung sound signals and exhibits significant advantages in terms of standardized evaluation metrics when compared to contrast methods.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"32 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140882623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluation of features and channels of electroencephalographic signals for biometric systems 评估生物识别系统的脑电信号特征和通道

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-05-01 DOI: 10.1186/s13634-024-01155-x

Dustin Carrión-Ojeda, Paola Martínez-Arias, Rigoberto Fonseca-Delgado, Israel Pineda, Héctor Mejía-Vallejo

{"title":"Evaluation of features and channels of electroencephalographic signals for biometric systems","authors":"Dustin Carrión-Ojeda, Paola Martínez-Arias, Rigoberto Fonseca-Delgado, Israel Pineda, Héctor Mejía-Vallejo","doi":"10.1186/s13634-024-01155-x","DOIUrl":"https://doi.org/10.1186/s13634-024-01155-x","url":null,"abstract":"<p>Biometric systems are essential tools in modern society where most of our personal information lives in digital form. Although there is a significant variety of biometrics, electroencephalogram (EEG) signals are a useful technique to guarantee that the person is alive, they are universal, and not falsifiable. Nevertheless, EEG processing needs to address some challenges to become a viable technique to build production-ready biometric systems. These challenges include the adequate selection of features and channels that maximize the quality of the results and optimize resources. This work provides an analysis of which are the most important features and channels for the correct operation of a biometric system. The experimental analysis worked with two datasets and evaluated 19 features belonging to three groups, wavelet-based, spectral, and complexity. Five classifiers were trained: multilayer perceptron, AdaBoost, random forest, support vector machine, and K-nearest neighbors. The results found that the best feature for developing a biometric system is the standard deviation extracted from the coefficients of a three-level discrete wavelet transform. Additionally, the experimental results with the two datasets showed that the proposed method for channel selection can reduce the necessary number of channels while maintaining its performance. Our results, from one of the datasets, showed a reduction of 21 channels (from 32 to 11) and indicated that the best channels to develop biometric systems seem to be those located on the central area of the scalp.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"24 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140829103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust point cloud registration for map-based autonomous robot navigation 基于地图的自主机器人导航的稳健点云注册

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-04-30 DOI: 10.1186/s13634-024-01153-z

Amit Efraim, Joseph M. Francos

{"title":"Robust point cloud registration for map-based autonomous robot navigation","authors":"Amit Efraim, Joseph M. Francos","doi":"10.1186/s13634-024-01153-z","DOIUrl":"https://doi.org/10.1186/s13634-024-01153-z","url":null,"abstract":"<p>Autonomous navigation in large-scale and complex environments in the absence of a GPS signal is a fundamental challenge encountered in a variety of applications. Since 3-D scans provide inherent robustness to ambient illumination changes and the type of the surface texture, we present Point Cloud Map-based Navigation (PCMN), a robust robot navigation system, based exclusively on 3-D point cloud registration between an acquired observation and a stored reference map. It provides a drift-free navigation solution, equipped with a failed registration detection capability. The backbone of the navigation system is a robust point cloud registration method, of the acquired observation to the stored reference map. The proposed registration algorithm follows a hypotheses generation and evaluation paradigm, where multiple statistically independent hypotheses are generated from local neighborhoods of putative matching points. Then, hypotheses are evaluated using a multiple consensus analysis that integrates evaluation of the point cloud feature correlation and a consensus test on the Special Euclidean Group SE(3) based on independent hypothesized estimates. The proposed PCMN is shown to achieve significantly better performance than state-of-the-art methods, both in terms of place recognition recall and localization accuracy, achieving submesh resolution accuracy, both for indoor and outdoor settings.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"25 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140842346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-Triggered confidentiality fusion estimation against eavesdroppers in cyber-physical systems 针对网络物理系统中窃听者的事件触发保密性融合估计

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-04-25 DOI: 10.1186/s13634-024-01124-4

Daxing Xu, Zhiqiang Chen, Hailun Wang

引用次数: 0

Anti-interrupted-sampling repeater jamming method based on frequency agility waveform and sparse recovery 基于频率敏捷波形和稀疏恢复的反中断采样中继器干扰方法

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-04-22 DOI: 10.1186/s13634-024-01149-9

Yunhao Ji, Shan Wei, Yaobing Lu

引用次数: 0

Reliable urban vehicle localization under faulty satellite navigation signals 故障卫星导航信号下可靠的城市车辆定位

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-04-20 DOI: 10.1186/s13634-024-01150-2

Shubh Gupta, Grace X. Gao

{"title":"Reliable urban vehicle localization under faulty satellite navigation signals","authors":"Shubh Gupta, Grace X. Gao","doi":"10.1186/s13634-024-01150-2","DOIUrl":"https://doi.org/10.1186/s13634-024-01150-2","url":null,"abstract":"<p>Reliable urban navigation using global navigation satellite system requires accurately estimating vehicle position despite measurement faults and monitoring the trustworthiness (or integrity) of the estimated location. However, reflected signals in urban areas introduce biases (or faults) in multiple measurements, while blocked signals reduce the number of available measurements, hindering robust localization and integrity monitoring. This paper presents a novel particle filter framework to address these challenges. First, a Bayesian fault-robust optimization task, formulated through a Gaussian mixture model (GMM) measurement likelihood, is integrated into the particle filter to mitigate faults in multiple measurement for enhanced positioning accuracy. Building on this, a novel test statistic leveraging the particle filter distribution and the GMM likelihood is devised to monitor the integrity of the localization by detecting errors exceeding a safe threshold. The performance of the proposed framework is demonstrated on real-world and simulated urban driving data. Our localization algorithm consistently achieves smaller positioning errors compared to existing filters under multiple faults. Furthermore, the proposed integrity monitor exhibits fewer missed and false alarms in detecting unsafe large localization errors.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"87 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140629582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A cloud-edge collaborative computing framework using potential games for space-air-ground integrated IoT 利用潜在游戏的云边协作计算框架，实现天-空-地一体化物联网

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-04-20 DOI: 10.1186/s13634-024-01122-6

Yuhuai Peng, Xiaoliang Guang, Xinyu Zhang, Lei Liu, Cemulige Wu, Lei Huang

{"title":"A cloud-edge collaborative computing framework using potential games for space-air-ground integrated IoT","authors":"Yuhuai Peng, Xiaoliang Guang, Xinyu Zhang, Lei Liu, Cemulige Wu, Lei Huang","doi":"10.1186/s13634-024-01122-6","DOIUrl":"https://doi.org/10.1186/s13634-024-01122-6","url":null,"abstract":"<p>As a critical component of space-air-ground integrated IoT, the aerial network provides highly reliable, low-latency and ubiquitous information services to ground users by virtue of their high mobility, easy deployment and low cost. However, the current computation and resource management model of air-ground integrated networks are insufficient to meet the latency demanding of emerging intelligent services such as autonomous systems, extended reality and haptic feedback. To tackle these challenges, we propose a computation offloading and optimization method based on potential game. First, we construct an cloud-edge collaborative computing model. Secondly, we construct Offloading Decision Objective Functions (ODOF) with the objective of minimum task processing latency and energy consumption. ODOF is proved to be a Mixed Inferior Nonlinear Programming (MINLP) problem, which is hard to solve. ODOF is converted to be a full potential game, and the Nash equilibrium solution exists. Then, a computational resource allocation algorithm based on Karush–Kuhn–Tucker (KKT) conditions is proposed to solve resource allocation problem. On this basis, a distributed game-based computational offloading algorithm is proposed to minimize the offloading cost. Extensive simulation results demonstrate that the convergence performance of the proposed algorithm is reduced by 50%, the convergence time is reduced by 13.3% and the average task processing delay is reduced by 10%.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"122 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140625521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Temporally-correlated massive access: joint user activity detection and channel estimation via vector approximate message passing 时相关大规模接入：通过向量近似信息传递联合检测用户活动和信道估计

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-04-16 DOI: 10.1186/s13634-024-01151-1

Yueyue Xiong, Wei Li

{"title":"Temporally-correlated massive access: joint user activity detection and channel estimation via vector approximate message passing","authors":"Yueyue Xiong, Wei Li","doi":"10.1186/s13634-024-01151-1","DOIUrl":"https://doi.org/10.1186/s13634-024-01151-1","url":null,"abstract":"<p>In the paper, we investigate a massive machine-type communication (mMTC), where numerous single-antenna users communicate with a single-antenna base station while being active. However, the status of user can undergoes multiple transitions between active and inactive states across whole consecutive intervals. Then, we formulate the problem of joint user activity detection and channel estimation within the dynamic compressed sensing (DCS) framework, considering the temporally-correlated user activity across the entire consecutive intervals. To be specific, we introduce a new hybrid vector approximate message passing algorithm for DCS (HyVAMP-DCS). The proposed algorithm comprises a VAMP block for estimating channel and a loopy belief propagation (LBP) block for detecting user activity. Moreover, these two blocks can exchange messages, enhancing the performance of both channel estimation and user activity detection. Importantly, compared to the fragile GAMP algorithm, VAMP is robust and applicable to a much broader class of large random matrices. Furthermore, the fixed points of VAMP’s state evolution align with the replica prediction of the minimum mean-squared error. The simulation results illustrate the superiority of HyVAMP-DCS, demonstrating its significant outperformance over HyGAMP-DCS.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"2012 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140609149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance evaluation of lung sounds classification using deep learning under variable parameters 参数可变情况下使用深度学习进行肺部声音分类的性能评估

IF 1.9 4区工程技术

EURASIP Journal on Advances in Signal Processing Pub Date : 2024-04-15 DOI: 10.1186/s13634-024-01148-w

Zhaoping Wang, Zhiqiang Sun

{"title":"Performance evaluation of lung sounds classification using deep learning under variable parameters","authors":"Zhaoping Wang, Zhiqiang Sun","doi":"10.1186/s13634-024-01148-w","DOIUrl":"https://doi.org/10.1186/s13634-024-01148-w","url":null,"abstract":"<p>It is desired to apply deep learning models (DLMs) to assist physicians in distinguishing abnormal/normal lung sounds as quickly as possible. The performance of DLMs depends on feature-related and model-related parameters heavily. In this paper, the relationship between performance and feature-related parameters of a DLM, i.e., convolutional neural network (CNN) is analyzed through experiments. ICBHI 2017 is selected as the lung sounds dataset. The sensitivity analysis of classification performance of the DLM on three parameters, i.e., the length of lung sounds frame, overlap percentage (OP) of successive frames and feature type, is performed. An augmented and balanced dataset is acquired by the way of white noise addition, time stretching and pitch shifting. The spectrogram and mel frequency cepstrum coefficients of lung sounds are used as features to the CNN, respectively. The results of training and test show that there exists significant difference on performance among various parameter combinations. The parameter OP is performance sensitive. The higher OP, the better performance. It is concluded that for fixed sampling frequency 8 kHz, frame size 128, OP 75% and spectrogram feature is optimum under which the performance is relatively better and no extra computation or storage resources are required.</p>","PeriodicalId":11816,"journal":{"name":"EURASIP Journal on Advances in Signal Processing","volume":"21 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140601355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0