IEEE Signal Processing Letters最新文献_第9页

Minimum Total Quaternion Error Entropy Filtering With Fiducial Points Against Asymmetric Noise 针对非对称噪声的最小四元数误差熵基点滤波

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3515813

Dongyuan Lin;Peng Cai;Xiaofeng Chen;Yunfei Zheng;Shiyuan Wang

引用次数: 0

Complex Gaussian Processes for Regression and Their Connection to WLMMSE 回归的复杂高斯过程及其与WLMMSE的关系

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3515818

Rafael Boloix-Tortosa;Juan José Murillo-Fuentes

{"title":"Complex Gaussian Processes for Regression and Their Connection to WLMMSE","authors":"Rafael Boloix-Tortosa;Juan José Murillo-Fuentes","doi":"10.1109/LSP.2024.3515818","DOIUrl":"https://doi.org/10.1109/LSP.2024.3515818","url":null,"abstract":"The Gaussian process (GP) is a well-established Bayesian nonparametric tool for inference in nonlinear estimation problems. When GPs are used for regression, the goal is to estimate a target signal \u0000<inline-formula><tex-math>${y}$</tex-math></inline-formula>\u0000 from an input vector \u0000<inline-formula><tex-math>$mathbf {x}$</tex-math></inline-formula>\u0000 without assuming that they are linearly related, but with a probabilistic model \u0000<inline-formula><tex-math>$p({y}|mathbf {x})$</tex-math></inline-formula>\u0000 that is Gaussian distributed. Therefore, GPs can be understood as a natural nonlinear extension to MMSE estimation. For real-valued GPs, this has been analyzed in the existing literature, and it is concluded that they are the natural nonlinear Bayesian extension to the linear minimum mean-squared error (LMMSE) estimation. In this letter, we show that, consequently, complex-valued GP regression (GPR) models are the natural nonlinear Bayesian extension of the widely linear minimum mean squared-error (WLMMSE) estimation. As in the real-valued case, complex-valued GPs are able to better model many regression problems by making use of the information that the complementary kernel or pseudo-kernel provides.","PeriodicalId":13154,"journal":{"name":"IEEE Signal Processing Letters","volume":"32 ","pages":"386-390"},"PeriodicalIF":3.2,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10791914","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142925449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal Sensor Decision Rules for Quantized-but-Uncoded Distributed Detection 量化非编码分布式检测的最优传感器决策规则

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3514798

Lei Cao;Ramanarayanan Viswanathan

引用次数: 0

Radar Signal Intra-Pulse Modulation Recognition Based on Point Cloud Network 基于点云网络的雷达信号脉冲内调制识别

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3514796

Tao Chen;Hao Tian;Yingming Liu;Yihan Xiao;Boyi Yang

引用次数: 0

Audio-Based Kinship Verification Using Age Domain Conversion 基于音频的年龄域转换亲属关系验证

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3515811

Qiyang Sun;Alican Akman;Xin Jing;Manuel Milling;Björn W. Schuller

引用次数: 0

Hybrid Self-Aligned Fusion With Dual-Weight Attention Network for Alzheimer's Detection 双权注意网络混合自对准融合检测阿尔茨海默病

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3514803

Ning Wang;Minghui Wu;Wenchao Gu;Zhilei Chai

{"title":"Hybrid Self-Aligned Fusion With Dual-Weight Attention Network for Alzheimer's Detection","authors":"Ning Wang;Minghui Wu;Wenchao Gu;Zhilei Chai","doi":"10.1109/LSP.2024.3514803","DOIUrl":"https://doi.org/10.1109/LSP.2024.3514803","url":null,"abstract":"Dementia, particularly Alzheimer's disease (AD), affects millions of elderly individuals worldwide. Traditionally, interview data, including audio recordings and transcripts, is used to train Artificial Intelligence models for the automatic detection of AD patterns. In this work, we introduce a novel attention-weighted image set, where each image integrates text-image relevance with focused areas from the Cookie Theft picture, derived from the corresponding description. Furthermore, we propose a novel multimodal architecture, Hybrid Self-Aligned Fusion with Dual-Weight Attention Network (HSAF-DWAN), to predict AD, using audio recordings, transcripts, and corresponding attention-weighted images. This architecture consists of two key modules: an Intra-Modality Self-Alignment (IMSA) module, which captures relationships within a single modality, and a Dual-Weight Cross-Modality Attention (DW-CMA) module, which effectively fuses cross-modality data through a dual-weight mechanism, incorporating an optimized cross-attention and secondary weighting. Extensive experiments conducted on the Cookie Theft corpus from DementiaBank demonstrate that our method outperforms state-of-the-art models, achieving an accuracy of 86.71% and an F1 score of 88.15%.","PeriodicalId":13154,"journal":{"name":"IEEE Signal Processing Letters","volume":"32 ","pages":"346-350"},"PeriodicalIF":3.2,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890385","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

Critical-Area-Based Stochastic DoS Attack Strategy Design Against Remote State Estimation in Multi-Area Power Systems 基于临界区域的多区域电力系统远程状态估计随机DoS攻击策略设计

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3515458

Guowei Liu;Engang Tian;Xia Zhao;Huwei Chen

{"title":"Critical-Area-Based Stochastic DoS Attack Strategy Design Against Remote State Estimation in Multi-Area Power Systems","authors":"Guowei Liu;Engang Tian;Xia Zhao;Huwei Chen","doi":"10.1109/LSP.2024.3515458","DOIUrl":"https://doi.org/10.1109/LSP.2024.3515458","url":null,"abstract":"This letter focuses on the design of a novel critical-area-based (CAB) stochastic denial-of-service (DoS) attack strategy aimed at diminishing the quality of remote state estimation in multi-area power systems. This attack strategy features two main characteristics: firstly, unlike most existing DoS attack models which typically overlook system information, the proposed CAB stochastic DoS attack strategy can selectively target critical areas of the power system, and the more severe impacts on system performance are expected. Secondly, the proposed attack strategy is stochastic, offering enhanced concealment compared to continuous or uniformly distributed DoS attack models. Furthermore, when the attacker faces energy constraints, an analytical relationship between the upper bound of the attack parameter and the expected total number of attacks is derived. Simulation results conducted on IEEE 39-bus and 118-bus systems validate that, compared to existing models, the proposed CAB stochastic DoS attack strategy induces more substantial disruptions in power system estimation quality, thus confirming its effectiveness from the attacker's perspective.","PeriodicalId":13154,"journal":{"name":"IEEE Signal Processing Letters","volume":"32 ","pages":"291-295"},"PeriodicalIF":3.2,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142890384","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

Optimal Transmission Schedule With Privacy Preservation for Cyber-Physical System Against Eavesdropping Attack 具有隐私保护的网络物理系统防窃听最优传输调度

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3514793

Zengwang Jin;Menglu Ma;Zhen Wang;Changyin Sun

引用次数: 0

Stochastic Analysis of FxLMS Algorithm for Feedback Active Noise Control 反馈主动噪声控制FxLMS算法的随机分析

IF 3.2 2区工程技术

IEEE Signal Processing Letters Pub Date : 2024-12-11 DOI: 10.1109/LSP.2024.3514792

Cong Wang;Ming Wu;Shuang Zhou;Jun Yang

引用次数: 0

List of Reviewers 审稿人名单