检索结果-内蒙古大学图书馆

A New Robot Navigation Algorithm Based on Bi-Directional Collaborative Ant Colony Optimization

IEEE SENSORS JOURNAL 2025年第8期25卷 14295-14306页

作者： Chen, Xufei Hu, Yaowei Tang, Pingping Zhang, Hui Jin, Jiong Mao, Shiwen Anhui Normal Univ Sch Phys & Elect Informat Wuhu 241002 Peoples R China Nanjing Univ Posts & Telecommun Sch Commun & Informat Engn Nanjing 210003 Peoples R China Swinburne Univ Technol Sch Engn Melbourne Vic 3122 Australia Auburn Univ Dept Elect & Comp Engn Auburn AL 36849 USA

Swarm intelligence has been widely adopted and successfully applied in the field of autonomous robot navigation. Among various swarm intelligence algorithms, ant colony optimization (ACO) has shown significant potential in addressing complex navigation challenges. However, ACO faces challenges, for example, unclear initial search direction, slow convergence, limited ant flexibility, and the need to simplify robot motion control. To address these challenges, this article presents a novel bi-directional collaborative ACO (BC-ACO) algorithm with key innovations. First, the algorithm adopts a bi-directional ant colony with forward and reverse populations, achieving effective route planning through collaborative decision-making. Second, the algorithm employs an adaptive step-size strategy and a stage-based exploration ant quantity adjustment method. These innovations optimize the balance between exploration and exploitation, accelerate convergence, and address the inefficiencies of traditional ACO methods. Additionally, this article improves the heuristic function by integrating a node distance index within the bi-directional ant colony, guiding the transition of ants between nodes and further accelerating convergence. Simulation results show that BC-ACO reduces the computation time by 73.97% and improves the convergence stability by 63.64% compared to standard ACO. Additionally, BC-ACO successfully plans optimal paths, achieving a 20.85% reduction in path length. Further integration of a local quadratic segmented B-spline (LQ-S B-spline) curve results in paths with smooth transitions, reducing robot motion complexity. In summary, BC-ACO achieves fast global convergence, high stability, and short computation time.

关键词： Heuristic algorithms Bidirectional control Convergence Splines (mathematics) Robots Optimization Navigation Indexes signal processing algorithms Collaboration Bi-directional ant colony collaborative decision-making node distance index segmented B-spline stage-based exploration ant quantity adjustment

来源：评论

学校读者我要写书评

暂无评论

Bayes Optimal Learning in High-Dimensional Linear Regression With Network Side Information

引用

IEEE TRANSACTIONS ON INFORMATION THEORY 2025年第1期71卷 565-591页

作者： Nandy, Sagnik Sen, Subhabrata Univ Chicago Dept Stat Chicago IL 60637 USA Harvard Univ Dept Stat Cambridge MA 02138 USA

Supervised learning problems with side information in the form of a network arise frequently in applications in genomics, proteomics and neuroscience. For example, in genetic applications, the network side information can accurately capture background biological information on the intricate relations among the relevant genes. In this paper, we initiate a study of Bayes optimal learning in high-dimensional linear regression with network side information. To this end, we first introduce a simple generative model (called the Reg-Graph model) which posits a joint distribution for the supervised data and the observed network through a common set of latent parameters. Next, we introduce an iterative algorithm based on Approximate Message Passing (AMP) which is provably Bayes optimal under very general conditions. In addition, we characterize the limiting mutual information between the latent signal and the data observed, and thus precisely quantify the statistical impact of the network side information. Finally, supporting numerical experiments suggest that the introduced algorithm has excellent performance in finite samples.

关键词： Bayes methods Message passing Mutual information signal processing algorithms Numerical models Limiting Data models Approximation algorithms Slabs Iterative methods Linear regression random networks approximate message passing mutual information variable selection

来源：评论

学校读者我要写书评

暂无评论

CUSE-TD Algorithm for Precision Detection of Coherent and Uncorrelated signals

引用

IEEE ACCESS 2025年 13卷 11307-11319页

作者： Dakulagi, Rohini Raushan, Ravi Dutta, Soham Alosaimi, Mohammed Theeb Villagomez-Galindo, Miguel Natl Inst Technol Karnataka Dept Elect & Elect Engn Mangaluru 575025 Karnataka India Manipal Acad Higher Educ Dept Elect & Elect Engn Manipal Inst Technol Manipal 576104 Karnataka India King Saud bin Abdulaziz Univ Hlth Sci Coll Sci & Hlth Profess Riyadh 11426 Saudi Arabia Minist Natl Guard Hlth Affairs King Abdullah Int Med Res Ctr Riyadh 11481 Saudi Arabia Univ Michoacana Mech Engn Fac Morelia 58000 Michoacan Mexico

This paper presents a novel algorithm, Coherent and Uncorrelated Sources Estimation using Tensor Decomposition (CUSE-TD), designed to enhance the accuracy of Direction of Arrival (DOA) estimation in Multiple-Input Multiple-Output (MIMO) systems. The CUSE-TD algorithm addresses the complex challenge of estimating both coherent and uncorrelated sources by leveraging advanced sensor-driven tensor decomposition techniques, with an emphasis on Tucker decomposition. By meticulously analyzing factor matrices derived from sensor data, the algorithm effectively decodes intricate spatiotemporal patterns within the received tensor, offering precise source estimation even in scenarios where the number and nature of the sources are unknown. The paper provides an in-depth assessment of the algorithm's performance, highlighting its computational efficiency and ability to handle diverse sensor-driven scenarios. Extensive simulations in intricate sensing environments demonstrate the algorithm's robustness, affirming its potential to significantly improve DOA estimation accuracy in MIMO systems across a wide range of operational conditions. The usefulness of the CUSE-TD algorithm lies in its applicability CUSE -TD to real-world MIMO systems, particularly in complex environments such as radar, wireless communications, and surveillance systems, where accurate source detection is critical for operational effectiveness. Its adaptability to varying sensor configurations and source conditions makes it a powerful tool for enhancing overall system reliability and performance.

关键词： Direction-of-arrival estimation Tensors Estimation signal processing algorithms Accuracy MIMO radar Array signal processing Matrix decomposition signal resolution Radar CUSE-TD algorithm direction of arrival (DOA) estimation multiple-input multiple-output (MIMO) systems tensor decomposition Tucker decomposition coherent sources uncorrelated sources spatiotemporal sensor data computational complexity sensor arrays

来源：评论

学校读者我要写书评

暂无评论

Communication-Efficient Federated Optimization Over Semi-Decentralized Networks

引用

IEEE TRANSACTIONS ON signal AND INFORMATION processing OVER NETWORKS 2025年 11卷 147-160页

作者： Wang, He Chi, Yuejie Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

In large-scale federated and decentralized learning, communication efficiency is one of the most challenging bottlenecks. While gossip communication-where agents can exchange information with their connected neighbors-is more cost-effective than communicating with the remote server, it often requires a greater number of communication rounds, especially for large and sparse networks. To tackle the trade-off, we examine the communication efficiency under a semi-decentralized communication protocol, in which agents can perform both agent-to-agent and agent-to-server communication in a probabilistic manner. We design a tailored communication-efficient algorithm over semi-decentralized networks, referred to as PISCO, which inherits the robustness to data heterogeneity thanks to gradient tracking and allows multiple local updates for saving communication. We establish the convergence rate of PISCO for nonconvex problems and show that PISCO enjoys a linear speedup in terms of the number of agents and local updates. Our numerical results highlight the superior communication efficiency of PISCO and its resilience to data heterogeneity and various network topologies.

关键词： Servers Optimization Convergence Probabilistic logic Network topology Vectors signal processing algorithms Robustness Protocols Information processing Communication efficiency semi-decentralized networks probabilistic communication models local updates

来源：评论

学校读者我要写书评

暂无评论

Distributed Continuous-Time Optimization With Uncertain Time-Varying Quadratic Cost Functions

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2025年第2期55卷 1526-1536页

作者： Jiang, Liangze Wu, Zheng-Guang Wang, Lei Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China

This article studies distributed continuous-time optimization for time-varying quadratic cost functions with uncertain parameters. We first propose a centralized adaptive optimization algorithm using partial information of the cost function. It can be seen that even if there are uncertain parameters in the cost function, exact optimization can still be achieved. To solve this problem in a distributed manner when different local cost functions have identical Hessians, we propose a novel distributed algorithm that cascades the fixed-time average estimator and the distributed optimizer. We remove the requirement for the upper bounds of certain complex functions by integrating state-based gains in the proposed design. We further extend this result to address the distributed optimization where the time-varying cost functions have nonidentical Hessians. We prove the convergence of all the proposed algorithms in the global sense. Numerical examples verify the proposed algorithms.

关键词： Cost function Heuristic algorithms Costs Time-varying systems signal processing algorithms Prediction algorithms Vectors Information exchange Eigenvalues and eigenfunctions Upper bound Adaptive gain continuous-time optimization distributed optimization quadratic function time-varying cost function uncertainties

来源：评论

学校读者我要写书评

暂无评论

Distributed Multi-Kernel Maximum Correntropy State-Constrained Kalman Filter Under Deception Attacks

引用

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2025年第1期12卷 533-546页

作者： Wang, Guoqing Zhu, Zhaolei Yang, Chunyu Ma, Lei Dai, Wei Chen, Xinkai China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221116 Peoples R China Shibaura Inst Technol Dept Elect & Informat Syst Saitama 3378570 Japan

In this paper, we investigate the distributed robust state estimation of non-Gaussian systems under unknown deception attacks with the imprecise constraint information. Leveraging the advantage of multi-kernel maximum correntropy criterion (MK-MCC) in non-Gaussian signal processing, a novel maximum-a-posterior like utility function (MAP-LUF) is designed inspired by the traditional 2-norm form cost function, where the inaccurate constraint information is taken into consideration. The direct solution of MAP-LUF gives rise to the centralized MK-MCC based state-constrained Kalman filter (C-MKMCSCKF) through fixed point iteration. Subsequently, the corresponding distributed algorithm is obtained by incorporating the consensus average in the computation of sum terms existing in the C-MKMCSCKF algorithm, which enables local information sharing to approximate the centralized estimation accuracy. Furthermore, we also establish the connection between the proposed centralized algorithm and the Banach theorem through dimension extension, and provide the convergence condition. The effectiveness of our proposed algorithms is validated through comparisons with related works in typical target tracking scenarios over sensor network.

关键词： Noise State estimation Vectors signal processing algorithms Cost function Accuracy Target tracking Kernel Kalman filters Convergence Deception attacks distributed Kalman filter multi-kernel correntropy robust state estimation sensor networks state constraint

来源：评论

学校读者我要写书评

暂无评论

Event-Triggered State Estimation Through Confidence Level

引用

IEEE TRANSACTIONS ON signal processing 2025年 73卷 1337-1350页

作者： Liu, Wei Zhejiang Gongshang Univ Sch Informat & Elect Engn Hangzhou 310018 Peoples R China

This paper considers the state estimation problem for discrete-time linear systems under event-triggered scheme. In order to improve performance, a novel event-triggered scheme based on confidence level is proposed using the chi-square distribution and mild regularity assumption. In terms of the novel event-triggered scheme, a minimum mean squared error (MMSE) state estimator is proposed using some results presented in this paper. Two algorithms for communication rate estimation of the proposed MMSE state estimator are developed where the first algorithm is based on information with one-step delay, and the second algorithm is based on information with two-step delay. The performance and effectiveness of the proposed MMSE state estimator and the two communication rate estimation algorithms are illustrated using a target tracking scenario.

关键词： Event detection Sensors State estimation Delays signal processing algorithms Covariance matrices Upper bound Prediction algorithms Costs Vectors Event-triggered state estimation, confidence level communication rate estimation discrete-time linear systems sensor networks

来源：评论

学校读者我要写书评

暂无评论

Robust Phase Retrieval by Alternating Minimization

引用

IEEE TRANSACTIONS ON signal processing 2025年 73卷 40-54页

作者： Kim, Seonho Lee, Kiryung Ohio State Univ Dept ECE Columbus OH 43210 USA

We consider a least absolute deviation (LAD) approach to the robust phase retrieval problem that aims to recover a signal from its absolute measurements corrupted with sparse noise. To solve the resulting non-convex optimization problem, we propose a robust alternating minimization (Robust-AM) derived as an unconstrained Gauss-Newton method. To solve the inner optimization arising in each step of Robust-AM, we adopt two computationally efficient methods. We provide a non-asymptotic convergence analysis of these practical algorithms for Robust-AM under the standard Gaussian measurement assumption. These algorithms, when suitably initialized, are guaranteed to converge linearly to the ground truth at an order-optimal sample complexity with high probability while the support of sparse noise is arbitrarily fixed and the sparsity level is no larger than 1/4. Additionally, through comprehensive numerical experiments on synthetic and image datasets, we show that Robust-AM outperforms existing methods for robust phase retrieval offering comparable theoretical performance guarantees.

关键词： Optimization signal processing algorithms Computational efficiency Minimization Extraterrestrial measurements Convergence Phase measurement Noise Computational modeling Vectors Phase retrieval outliers least absolute deviation linear program convex optimization

来源：评论

学校读者我要写书评

暂无评论

Dual Lawson Norm-Based Robust DOA Estimation for RIS-Aided Wireless Communication Systems

引用

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2025年第1期61卷 582-592页

作者： Yu, Canping Li, Yingsong Li, Liping Huang, Zhixiang Wu, Qingqing de Lamare, Rodrigo Anhui Univ Key Lab Intelligent Comp & Signal Proc Minist Educ Hefei 230601 Peoples R China Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China Pontifical Catholic Univ Rio De Janeiro PUC Rio Ctr Telecommun Res CE TUC BR-22451900 Gavea Brazil Univ York Sch Phys Engn & Technol York YO10 5DD England

Reconfigurable intelligent surfaces (RIS) can actively perform beamforming and have become a crucial enabler for the wireless systems in the future. The direction-of-arrival (DOA) estimates of RIS received signals can help design the reflection control matrix and improve communication quality. In this article, we design an RIS-assisted system and propose a robust Lawson norm-based multiple-signal-classification DOA estimation algorithm for impulsive noise environments, which is divided into two parts: First, the nonconvex Lawson norm is used as the error criterion along with a regularization constraint to formulate the optimization problem. Then, a Bregman distance-based alternating-direction-method-of-multipliers is used to solve the problem and recover the desired signal. The second part is to use the multiple-signal-classification to find out the DOAs of targets based on their sparsity in the spatial domain. In addition, we also propose an RIS control matrix optimization strategy that requires no channel state information, which effectively enhances the strength of desired signals and improves the performance of the devised algorithm. A Cram & eacute;r-Rao-lower-bound of the proposed DOA estimation algorithms is presented and verifies the feasibility of the algorithm. Simulated results show that the created robust DOA estimate algorithm realized using the Lawson norm can effectively suppress the impact of large outliers caused by impulsive noise on the estimation results, outperforming existing methods.

关键词： Direction-of-arrival estimation Estimation Noise Wireless communication signal processing algorithms Vectors Reconfigurable intelligent surfaces Alternating-direction-method-of-multipliers (ADMM) Cramer-Rao-lower-bound (CRLB) direction-of-arrival (DOA) estimation Lawson norm multiple-signal-classification (MUSIC) reconfigurable intelligent surfaces (RIS)

来源：评论

学校读者我要写书评

暂无评论

A Novel Tracker of Adaptive Directional Ridge Separation and Prediction for Detecting Whistles

引用

IEEE JOURNAL OF OCEANIC ENGINEERING 2025年第1期50卷 13-24页

作者： Miao, Yongchun Li, Jianghui Li, Yingsong Anhui Univ Key Lab Intelligent Comp & Signal Proc Minist Educ Hefei 230601 Peoples R China MNR Key Lab Southeast Coast Marine Informat Intelligen Zhangzhou 363000 Peoples R China Xiamen Univ Coll Ocean & Earth Sci State Key Lab Marine Environm Sci Xiamen 361102 Peoples R China

Whistle detection of marine mammal signals with close and overlapping components of varying amplitudes is a key task for overlapping source separation. In this article, we propose a novel tracker, called adaptive directional ridge separation and prediction, for detecting whistles, which are typically analyzed using a time-frequency (TF) representation. Inspired by TF reassignment, a new reassignment scheme based on time-scale changes is developed to acquire instantaneous TF points with high energy concentration. To address the mutual interference among various types of components, a tone-pulse separation model is introduced for the aliased TF components, utilizing these instantaneous TF points and instantaneous rotating operators. An adaptive directional ridge predictor is established for application in automatic overlapping whistle detection, ensuring unbroken detection even when a whistle becomes nearly indistinguishable in the TF representation. Experimental results, obtained using both a simulated signal and recorded calls of marine mammals, demonstrate the superiority of the proposed method compared to other state-of-the-art methods. This method is capable of performing whistle detection and separating overlapping sources even in the presence of splash noises, which may cause partial distortion or disconnection of components from the TF representation.

关键词： Chirp Time-frequency analysis signal processing algorithms Noise Jacobian matrices Complexity theory Whales Taylor series Source separation Predictive models Adaptive directional ridge prediction (ADRP) instantaneous rotating operator (IRO) time-frequency (TF) representation tone-pulse separation (TPS) whistle detection

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：