Signal Processing最新文献_第3页

A novel Gaussian-Student’s t-Skew mixture distribution based Kalman filter 基于高斯-学生 t-Skew 混合分布的新型卡尔曼滤波器

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-19 DOI: 10.1016/j.sigpro.2024.109787

Han Zou , Sunyong Wu , Qiutiao Xue , Xiyan Sun , Ming Li

引用次数: 0

Waveform agile MIMO radar fast waveform design based on random arrangement of pulse slices 基于脉冲片随机排列的波形敏捷 MIMO 雷达快速波形设计

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-18 DOI: 10.1016/j.sigpro.2024.109784

Ben Niu, Yongbo Zhao, Derui Tang

引用次数: 0

Specific and coupled double consistency multi-view subspace clustering with low-rank tensor learning 利用低阶张量学习进行特定和耦合双一致性多视角子空间聚类

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-17 DOI: 10.1016/j.sigpro.2024.109803

Tong Wu, Gui-Fu Lu

{"title":"Specific and coupled double consistency multi-view subspace clustering with low-rank tensor learning","authors":"Tong Wu, Gui-Fu Lu","doi":"10.1016/j.sigpro.2024.109803","DOIUrl":"10.1016/j.sigpro.2024.109803","url":null,"abstract":"<div><div>Multi-view clustering (MVC) has gained widespread attention due to its ability to utilize different features from different views. However, the existing MVC methods fail to fully exploit the consistency across multiple views, leading to information loss. Additionally, the performance of the algorithms is not satisfactory due to the inherent noise in the data. To address the above-mentioned issues, this paper proposes the specific and coupled double consistency multi-view subspace clustering with low-rank tensor learning (SCDCMV) method. Specifically, firstly, we simultaneously incorporate the consistency and specificity of multiple views into self-expressive learning. However, the information within the consistency matrix has not been fully utilized, and there still exists some noise. Then, the obtained consistency matrix is once again integrated into self-expressive learning to obtain a new consistency matrix. Thirdly, we combine the two consistency matrices into a tensor and constrain it using tensor nuclear norm (TNN). Then, under the constraint of TNN, the two consistency matrices mutually reinforce each other, which helps fully utilize the consistency information and reduce the impact of noise, ultimately leading to better clustering results. Ultimately, these three steps constitute a framework that is tackled utilizing the augmented Lagrange multiplier method. The performance of SCDCMV has improved by 55.94 %. Experimental results on different datasets indicate that the SCDCMV algorithm outperforms state-of-the-art algorithms. In other words, these experimental results validate the importance of effectively utilizing consistent information from multiple views while reducing the impact of noise. The code is publicly available at <span><span>https://github.com/TongWuahpu/SCDCMV</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109803"},"PeriodicalIF":3.4,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Depth gate tracking method based on historical sounding results in MBES

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-17 DOI: 10.1016/j.sigpro.2024.109808

Tian Zhou Member, IEEE , Weijia Yuan , Maria S. Greco Fellow, IEEE , Fulvio Gini Fellow, IEEE

{"title":"Depth gate tracking method based on historical sounding results in MBES","authors":"Tian Zhou Member, IEEE , Weijia Yuan , Maria S. Greco Fellow, IEEE , Fulvio Gini Fellow, IEEE","doi":"10.1016/j.sigpro.2024.109808","DOIUrl":"10.1016/j.sigpro.2024.109808","url":null,"abstract":"<div><div>Gate tracking technology plays a crucial role in the autonomous detection of multi-beam echo sounding. The quality of the tracking algorithm directly impacts the quality of the estimate data. Here, we propose a new method for depth gate tracking in multi-beam echo sounding based on the assumption that historical sounding results are geometrically similar to the current ping results. Considering Hausdorff distance measures how far two subsets of a metric space are from each other. An evaluation method based on the concept of similarity distance that relies on the Modified Hausdorff distance is proposed here to measure the similarity between the detection results of different pings and determine the maximum number of historical pings that can be tracked. Then, this model is combined with the iterative closest point registration algorithm to align the bathymetric results of historical pings to the current ping, eliminating the need for prior registration. The registered data are used to initialize the particle distribution in the tracking particle filter and a distance-weighted importance function is established for each beam. Validation on measured data has shown that the proposed method is effective in tracking seabed topography and providing stable gate tracking results.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109808"},"PeriodicalIF":3.4,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Euclidean direction search algorithm with maximum correntropy criterion for active noise control system 采用最大熵准则的欧氏方向搜索算法用于主动噪声控制系统

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-17 DOI: 10.1016/j.sigpro.2024.109759

Jie Wang , Lu Lu , Zongsheng Zheng , Kai-Li Yin , Yi Yu , Long Shi

引用次数: 0

Entropy-weighted manifold-adjusted transfer learning for cross-condition fault diagnosis with imbalanced and missing labels 针对标签不平衡和缺失的跨条件故障诊断的熵权流形调整迁移学习

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-16 DOI: 10.1016/j.sigpro.2024.109806

Ziyou Zhou, Wenhua Chen

{"title":"Entropy-weighted manifold-adjusted transfer learning for cross-condition fault diagnosis with imbalanced and missing labels","authors":"Ziyou Zhou, Wenhua Chen","doi":"10.1016/j.sigpro.2024.109806","DOIUrl":"10.1016/j.sigpro.2024.109806","url":null,"abstract":"<div><div>In industrial fault diagnosis, data imbalance, missing labels, and cross-condition scenarios increase complexity and challenges. While existing research has made progress in these areas, gaps remain in addressing cross-condition fault diagnosis with imbalanced and incomplete labels. To tackle this, we propose the entropy-weighted manifold alignment (E-WMA) method. First, we use sparse filtering techniques for manifold alignment to extract features with good separability from the source and target domains. Next, we adopt an entropy-weighted maximum mean discrepancy strategy to dynamically adjust sample weights based on label information entropy, which reduces distribution differences and mitigates data imbalance. Finally, we build a softmax regression classifier to train and evaluate the fault diagnosis model using the aligned features and adjusted sample weights, enhancing diagnostic accuracy and robustness. Extensive experiments on wind turbine planetary gearbox and bearing fault datasets validate our approach. The results show that our method effectively addresses cross-condition fault diagnosis amid data imbalance and missing labels. This can lead to more accurate fault detection in real-time operations, minimize unplanned downtime, and significantly reduce maintenance costs in industrial environments.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109806"},"PeriodicalIF":3.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 sparse low-rank matrix recovery strategy to deal with robust identification for multi-model systems with time-varying delays 处理具有时变延迟的多模型系统鲁棒识别的稀疏低阶矩阵恢复策略

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-15 DOI: 10.1016/j.sigpro.2024.109783

Junxia Ma , Ronghuan Li , Yujie Ma , Jing Chen

{"title":"A sparse low-rank matrix recovery strategy to deal with robust identification for multi-model systems with time-varying delays","authors":"Junxia Ma , Ronghuan Li , Yujie Ma , Jing Chen","doi":"10.1016/j.sigpro.2024.109783","DOIUrl":"10.1016/j.sigpro.2024.109783","url":null,"abstract":"<div><div>A robust identification problem for multi-model systems with time-vary delays is considered in this article, where the linear parameter varying model is employed to present the structure of the multi-model systems. To handle outliers in the collected data, we establish an observation model based on a robust principal component analysis (RPCA) algorithm for low-rank matrix recovery. Construct a high-dimensional information matrix using multi-batch measured data. Although this matrix is typically high-dimensional and low-rank, outliers cause it to become high-dimensional and high-rank. By applying the RPCA algorithm, we restore the information matrix to its low-rank form, thus isolating the pure collected data. This process allows us to select a batch of collected data as information vectors for parameter identification. A Markov chain model is established to describe the correlation between time delays. Given the complexity of optimizing log-likelihood functions directly, we derive the estimation problem of model parameters and time delays under the framework of the expectation maximization (EM) algorithm. Therefore, an EM identification algorithm based on RPCA (RPCA-EM) is derived. A numerical simulation and an example involving a continuous stirred tank reactor verify the effectiveness of the proposed RPCA-EM algorithm.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109783"},"PeriodicalIF":3.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Distributed filtering with time-varying topology: A temporal-difference learning approach in dual games 具有时变拓扑结构的分布式过滤：双重博弈中的时差学习方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-12 DOI: 10.1016/j.sigpro.2024.109772

Huiwen Xue , Jiwei Wen , Ruichao Li , Xiaoli Luan

{"title":"Distributed filtering with time-varying topology: A temporal-difference learning approach in dual games","authors":"Huiwen Xue , Jiwei Wen , Ruichao Li , Xiaoli Luan","doi":"10.1016/j.sigpro.2024.109772","DOIUrl":"10.1016/j.sigpro.2024.109772","url":null,"abstract":"<div><div>This study aims to develop a dual games (DGs) mechanism and implement a temporal difference learning (TDL) approach to address distributed filter design while considering network-induced time-varying topology from individual optimality and global equilibrium perspectives. In a detailed analysis, each filtering node (FN) treats its individual filtering action and exogenous disturbance as opposing elements, striving to determine the optimal policy while accounting for the worst-case scenario. This competition between FN and the disturbance culminates in a zero-sum game. Simultaneously, FN collaborates effectively with its neighbors to achieve consensus estimation, giving rise to a non-zero-sum game. Notably, an error-based filtering action is built to solve challenges posed by DGs. Ultimately, each FN attains its estimation at a minimum cost, and the entire distributed filtering network achieves the consensus estimation at a Nash equilibrium. Moreover, the transition probability correlation matrices (TPCMs) of the time-varying topology are obtained through direct observation of multi-episodes of topological transition trajectories. It has been proved that with a sufficiently ample number of episodes, TPCMs converge to their optimal values when TPs are known as apriori. Finally, a numerical example and an aero-engine system are presented to illustrate the effectiveness and practical potential of the proposed method.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109772"},"PeriodicalIF":3.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

RIS-aided integrated sensing and communication: Beamforming design and antenna selection RIS 辅助综合传感与通信：波束成形设计和天线选择

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-12 DOI: 10.1016/j.sigpro.2024.109771

Yuying Mai , Mateen Ashraf , Huiqin Du , Bo Tan

{"title":"RIS-aided integrated sensing and communication: Beamforming design and antenna selection","authors":"Yuying Mai , Mateen Ashraf , Huiqin Du , Bo Tan","doi":"10.1016/j.sigpro.2024.109771","DOIUrl":"10.1016/j.sigpro.2024.109771","url":null,"abstract":"<div><div>This work considers an integrated sensing and communication system, where a reconfigurable intelligent surface (RIS) is utilized to manage interference and radar signals. The sensors are attached to the RIS to sense multiple targets. A joint design of the base station transmit beamforming and RIS phase shift matrix is proposed to minimize total interference and maximize the worst received signal power at the RIS sensors. Due to highly coupled transmit beamforming and RIS phase matrices, the optimization problem is decoupled into two subproblems and solved iteratively by semidefinite programming and a manifold-based Riemannian steepest descent algorithm. We further design energy-aware beamforming to eliminate the interference induced by radar probing signals. Antenna selection with the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> norm is introduced to exclude redundant antennas while maintaining the sufficient multiple beams for multiple users and targets with minimized required antennas. Due to the nonconvexity of the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>-norm, we relax the number of active transmit antennas as a weighted <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-norm and employ a concave approximation for the constraint on the radar beampattern. Numerical results illustrate that the proposed algorithms can effectively reduce interference and strengthen the received signal power for radar sensing, achieving mutual benefit for communication and sensing performance.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109771"},"PeriodicalIF":3.4,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

MABDT: Multi-scale attention boosted deformable transformer for remote sensing image dehazing MABDT：用于遥感图像去毛刺的多尺度注意力增强可变形变换器

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-07 DOI: 10.1016/j.sigpro.2024.109768

Jin Ning, Jie Yin, Fei Deng, Lianbin Xie

{"title":"MABDT: Multi-scale attention boosted deformable transformer for remote sensing image dehazing","authors":"Jin Ning, Jie Yin, Fei Deng, Lianbin Xie","doi":"10.1016/j.sigpro.2024.109768","DOIUrl":"10.1016/j.sigpro.2024.109768","url":null,"abstract":"<div><div>Owing to the heterogeneous spatial distribution and non-uniform morphological characteristics of haze in remote sensing images (RSIs), conventional dehazing algorithms struggle to precisely recover the fine-grained details of terrestrial objects. To address this issue, a novel multi-scale attention boosted deformable Transformer (MABDT) tailored for RSI dehazing is proposed. This framework synergizes the multi-receptive field features elicited by convolutional neural network (CNN) with the long-term dependency features derived from Transformer, which facilitates a more adept restitution of texture and intricate detail information within RSIs. Firstly, spatial attention deformable convolution is introduced for computation of multi-head self-attention in the Transformer block, particularly in addressing complex haze scenarios encountered in RSIs. Subsequently, a multi-scale attention feature enhancement (MAFE) block is designed, tailored to capture local and multi-level detailed information features using multi-receptive field convolution operations, thereby accommodating non-uniform haze. Finally, a multi-level feature complementary fusion (MFCF) block is proposed, leveraging both shallow and deep features acquired from all encoding layers to augment each level of reconstructed image. The dehazing performance is evaluated on 6 open-source datasets, and quantitative and qualitative experimental results demonstrate the advancements of the proposed method in both metrical scores and visual quality. The source code is available at <span><span>https://github.com/ningjin00/MABDT</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109768"},"PeriodicalIF":3.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142658958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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