IEEE Transactions on Signal Processing最新文献_第5页

Vector Approximate Survey Propagation 矢量近似测量传播

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-09 DOI: 10.1109/tsp.2025.3607946

Qun Chen, Haochuan Zhang, Huimin Zhu

引用次数: 0

Underwater Acoustic Target Recognition Using Dictionary Learning-Based Feature Fusion and MD-GANs Data Augmentation 基于字典学习特征融合和MD-GANs数据增强的水声目标识别

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-09 DOI: 10.1109/tsp.2025.3607836

Xiaoli Du, Yintang Wen, Yangjun Liu, Fubo Chen, Haiyu Wang, Yuyan Zhang, Xiaoyuan Luo

引用次数: 0

Human Feedback Attack on Online RLHF: Attack and Robust Defense 在线RLHF的人反馈攻击：攻击与鲁棒防御

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-08 DOI: 10.1109/tsp.2025.3607114

Chenye Yang, Mo Lyu, Guanlin Liu, Lifeng Lai

引用次数: 0

Adaptive Social Learning for Slow Markov Chains 慢马尔科夫链的自适应社会学习

IF 5.8 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-08 DOI: 10.1109/TSP.2025.3606580

Malek Khammassi;Virginia Bordignon;Vincenzo Matta;Ali H. Sayed

{"title":"Adaptive Social Learning for Slow Markov Chains","authors":"Malek Khammassi;Virginia Bordignon;Vincenzo Matta;Ali H. Sayed","doi":"10.1109/TSP.2025.3606580","DOIUrl":"10.1109/TSP.2025.3606580","url":null,"abstract":"This paper studies the problem of interconnected agents collaborating to track a dynamic state from partially informative observations, where the state follows a slow finite-state Markov chain. While the centralized version of this problem is well understood, the decentralized setting warrants further exploration. This work aims to demonstrate that a decentralized social learning strategy can achieve the same error probability scaling law in the rare transitions regime as the optimal centralized solution. To study this problem, we focus on adaptive social learning (ASL), a recent strategy developed for non-stationary environments, and analyze its performance when the agents’ observations are governed by a hidden, slow Markov chain. Our study yields two key findings. First, we demonstrate that the ASL adaptation performance is closely linked to the dynamics of the underlying Markov chain, achieving a vanishing steady-state error probability when the average drift time of the Markov chain exceeds the ASL adaptation time. Second, we derive a closed-form upper bound for the ASL steady-state error probability in the rare transition regime, showing that it decays similarly to the optimal centralized solution. Simulations illustrate our theoretical findings and provide a comparative analysis with existing strategies.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"3671-3687"},"PeriodicalIF":5.8,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145017536","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 1.5-bit Quantization Scheme and Its Application to Direction Estimation 一种1.5位量化方案及其在方向估计中的应用

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-05 DOI: 10.1109/tsp.2025.3604889

Xicheng Lu, Wei Liu, Akram Alomainy

引用次数: 0

Score-Based Reverse Mean Propagation for Solving Inverse Problems 求解逆问题的基于分数的逆均值传播

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-04 DOI: 10.1109/tsp.2025.3605633

Zhipeng Xue, Penghao Cai, Xiaojun Yuan, Xiqi Gao

引用次数: 0

Sparse Decentralized Federated Learning 稀疏分散联邦学习

IF 5.8 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-01 DOI: 10.1109/TSP.2025.3603005

Shan Sha;Shenglong Zhou;Lingchen Kong;Geoffrey Ye Li

引用次数: 0

Orthogonal Fourier Analysis on Directed Acyclic Graphs via Möbius Total Variation 有向无环图的正交傅立叶分析Möbius全变分

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-01 DOI: 10.1109/tsp.2025.3603696

Vedran Mihal, Markus Püschel

引用次数: 0

A Unified Penalty Method for Maximum Likelihood Estimation of Gaussian and Student’s t GARCH 高斯极大似然估计与学生t GARCH的统一惩罚方法

IF 5.4 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-09-01 DOI: 10.1109/tsp.2025.3604632

Chenyu Gao, Ziping Zhao, Daniel P. Palomar

引用次数: 0

Over-Relaxed ADMM-Based Unitary Adaptive Beamforming Scheme With Lobe-Level Constraints 基于过松弛admm的叶级约束统一自适应波束形成方案

IF 5.8 2区工程技术

IEEE Transactions on Signal Processing Pub Date : 2025-08-29 DOI: 10.1109/TSP.2025.3603307

Siyuan Jiang;Shuai Liu;Feng-Gang Yan;Fulvio Gini;Maria Sabrina Greco;Ming Jin

{"title":"Over-Relaxed ADMM-Based Unitary Adaptive Beamforming Scheme With Lobe-Level Constraints","authors":"Siyuan Jiang;Shuai Liu;Feng-Gang Yan;Fulvio Gini;Maria Sabrina Greco;Ming Jin","doi":"10.1109/TSP.2025.3603307","DOIUrl":"10.1109/TSP.2025.3603307","url":null,"abstract":"The performance of adaptive beamforming may degrade dramatically in a highly dynamic environment, because the directions of arrival (DOAs) of targets and interferences can change rapidly. To address this problem, we propose here to introduce additional mainlobe-level and sidelobe-level constraints in the design problem, with the goal to broaden the mainlobe and the nulls of the beampattern. However, the solution of the resulting optimization problem with non-convex constraints has high computational complexity. To reduce it, we propose to transform the complex-valued non-convex constrained optimization problem into a real-valued convex constrained one by performing a unitary transformation, which is suitable for centro-symmetric arrays (CSA). Then, the problem is decomposed into multiple unconstrained optimization sub-problems that can be solved iteratively using the standard alternating direction method of multipliers (S-ADMM) method. To improve further the convergence speed, we then develop an over-relaxed ADMM (OR-ADMM) by exploiting the principle of relaxation. Numerical simulation demonstrates the robustness and the convergence speed improvements of the proposed OR-ADMM in a highly dynamic environment.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"3656-3670"},"PeriodicalIF":5.8,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144919540","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