检索结果-内蒙古大学图书馆

SAOFTRL: A Novel Adaptive Algorithmic Framework for Enhancing Online Portfolio Selection

IEEE TRANSACTIONS ON signal processing 2024年 72卷 5291-5305页

作者： Shi, Runhao Palomar, Daniel P. Hong Kong Univ Sci & Technol HKUST Clear Water Bay Hong Kong Peoples R China

Strongly Adaptive meta-algorithms (SA-meta) are popular in online portfolio selection due to their resilience in adversarial environments and adaptability to market changes. However, their application is often limited by high variance in errors, stemming from calculations over small intervals with limited observations. To address this limitation, we introduce the Strongly Adaptive Optimistic Follow-the-Regularized-Leader (SAOFTRL), an advanced framework that integrates the Optimistic Follow-the-Regularized-Leader (OFTRL) strategy into SA-meta algorithms to stabilize performance. SAOFTRL is distinguished by its novel regret bound, which provides a theoretical guarantee of worst-case performance in challenging scenarios. Additionally, we reimagine SAOFTRL within a mean-variance portfolio (MVP) framework, enhanced with shrinkage estimators and adaptive rolling windows, thereby ensuring reliable average-case performance. For practical deployment, we present an efficient SAOFTRL implementation utilizing the Successive Convex Approximation (SCA) method. Empirical evaluations demonstrate SAOFTRL's superior performance and expedited convergence when compared to existing benchmarks, confirming its effectiveness and efficiency in dynamic market conditions.

关键词： Portfolios signal processing algorithms Accuracy Robustness Prediction algorithms Standards Heuristic algorithms Benchmark testing Adaptation models Vectors Optimistic follow-the-regularized-leader strongly adaptive meta-algorithm mean-variance portfolio universal portfolio

来源：评论

学校读者我要写书评

暂无评论

Adaptive Parameter Selection Variational Mode Decomposition Based on Bayesian Optimization and Its Application to the Detection of ITSC in PMSM

引用

IEEE ACCESS 2024年 12卷 38594-38614页

作者： Xia, Yan-Kun Wang, Wan-Ting Li, Xin-Yang Xihua Univ Sch Elect & Elect Informat Engn Chengdu 610039 Peoples R China

Permanent magnet synchronous motor (PMSM) is a vital component of modern industry which is widely used in transport, aerospace and intelligent machinery. In the light of its relatively high frequency of inter-turn short circuit (ITSC) fault, it is valuable to detect the fault accurately and efficiently. Due to the convenience of motor vibration signal measurement, more attention has been paid to fault detection methods based on vibration signal. As a nonstationary, nonlinear signal, vibration signal is highly susceptible to external noise interference. Variational mode decomposition (VMD) has a wide range of applications in the field of nonlinear signal analysis, but the processing ability to the signal is affected by the parameter setting. Hence, a Bayesian optimized adaptive parameter selection variational mode decomposition (BOAPS-VMD) signal processing method is proposed and applied to detect the ITSC in PMSM. Firstly, the motor vibration signal is decomposed through BOAPS-VMD, and the intrinsic mode functions (IMFs) are obtained. Secondly, the cumulative variance contribution rate (C-VCR) is applied to identify the IMFs that contain fault signature information. Finally, using Hilbert transform (HT) to further analyze the IMFs that are identified. The results are output in 3D time-frequency diagrams to enhance the representation of fault signatures. The effectiveness and accuracy of the BOAPS-VMD were validated through the finite element simulation and experiment. The study shows that the BOAPS-VMD effectively improves the modal mixing phenomenon, has better noise robustness, improves the accuracy of fault detection, and has better engineering applicability.

关键词： Optimization signal processing algorithms Bayes methods Fault detection Vibrations Transforms signal resolution Parameter estimation Permanent magnet machines Hilbert space Permanent magnet synchronous motor (PMSM) fault detection variational mode decomposition (VMD) Bayesian optimization Hilbert transform (HT)

来源：评论

学校读者我要写书评

暂无评论

GNN-Based Beamforming for Sum-Rate Maximization in MU-MISO Networks

引用

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第8期23卷 9251-9264页

作者： Li, Yuhang Lu, Yang Ai, Bo Dobre, Octavia A. Ding, Zhiguo Niyato, Dusit Beijing Jiaotong Univ Sch Comp Sci & Technol Beijing 100044 Peoples R China Beijing Jiaotong Univ Collaborat Innovat Ctr Railway Traff Safety Beijing 100044 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Memorial Univ Fac Engn & Appl Sci St John NF A1C 5S7 Canada Khalifa Univ Dept Elect Engn & Comp Sci Abu Dhabi U Arab Emirates Nanyang Technol Univ Sch Comp Sci & Engn Singapore 639798 Singapore

The advantages of graph neural networks (GNNs) in leveraging the graph topology of wireless networks have drawn increasing attentions. This paper studies the GNN-based learning approach for the sum-rate maximization in multiple-user multiple-input single-output (MU-MISO) networks subject to the users' individual data rate requirements and the power budget of the base station (BS). By modeling the MU-MISO network as a graph, a GNN-based architecture named complex residual graph attention network (CRGAT) is proposed to directly map channel state information to beamforming vectors. The attention-enabled aggregation and the residual-assisted combination are adopted to enhance the learning capability and mitigate the oversmoothing issue. Furthermore, a novel activation function is proposed for the constraint due to the limited power budget at the BS. The CRGAT is trained via unsupervised learning with two proposed loss functions. An evaluation method is proposed for the learning-based approaches, based on which the effectiveness of the proposed CRGAT is validated in comparison with several convex optimization and learning based approaches. Numerical results are provided to reveal the advantages of the CRGAT including the millisecond-level response with limited optimality performance loss, the scalability to different number of users and power budgets, and the adaptability to different system settings.

关键词： Optimization Array signal processing signal processing algorithms Quality of service MISO communication Interference Message passing GNNs sum-rate maximization MU-MISO CRGAT

来源：评论

学校读者我要写书评

暂无评论

Direction Finding With Sparse Subarrays: Design, algorithms, and Analysis

引用

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2024年第6期60卷 8149-8165页

作者： Leite, Wesley S. de Lamare, Rodrigo C. Zakharov, Yuriy Liu, Wei Haardt, Martin Pontif Catholic Univ Rio de Janeiro PUC Rio Dept Elect Engn BR-22451900 Rio De Janeiro Brazil Univ York Sch Phys Engn & Technol York YO105DD England Hong Kong Polytech Univ Dept Elect & Elect Engn Hong Kong Peoples R China Ilmenau Univ Technol Commun Res Lab D-98693 Ilmenau Germany

This article proposes design techniques for partially calibrated sparse linear subarrays and algorithms to perform direction-of-arrival (DOA) estimation. First, we introduce array architectures that incorporate two distinct array categories, namely type-I and type-II arrays. The former breaks down a known sparse linear geometry into as many pieces as we need, and the latter employs each subarray such as it fits a preplanned sparse linear geometry. Moreover, we devise two DOA estimation algorithms that are suitable for partially calibrated array scenarios within the coarray domain. The algorithms are capable of estimating a greater number of sources than the number of available physical sensors, while maintaining the hardware and computational complexity within practical limits for real-time implementation. To this end, we exploit the intersection of projections onto affine spaces by devising the generalized coarray multiple signal classification (GCA-MUSIC) in conjunction with the estimation of a refined projection matrix related to the noise subspace, as proposed in the GCA root-MUSIC algorithm. An analysis is performed for the devised subarray configurations in terms of Degrees of Freedom, as well as the computation of the Cramer-Rao lower bound for the utilized data model, in order to demonstrate the good performance of the proposed methods. Simulations assess the performance of the proposed design methods and algorithms against existing approaches.

关键词： Estimation Direction-of-arrival estimation Geometry Sensor arrays Vectors signal processing algorithms Noise Direction-of-Arrival (DOA) estimation multiple signal classification (MUSIC) nonuniform linear arrays sparse linear array (SLA)

来源：评论

学校读者我要写书评

暂无评论

Quasi-Closed-Form algorithms for Spherical Angle-of-Arrival Source Localization

引用

IEEE TRANSACTIONS ON signal processing 2024年 72卷 432-448页

作者： Zhang, Tianyu Teng, Pengxiao Lyu, Jun Yang, Jun Chinese Acad Sci Inst Acoust Key Lab Noise & Vibrat Res Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

The ground curvature cannot be neglected when locating the source that generates long-range propagation signals, so the traditional angle-of-arrival (AOA) source localization evolves into spherical AOA source localization. For this problem, a quasi-closed-form algorithm, the spherical weighted pseudolinear estimator (SWPLE), is proposed in this paper. The analysis of the SWPLE reveals that the algorithm has bias problems. To mitigate the bias of the SWPLE, we propose an algorithm based on biased term estimation, the bias compensated spherical weighted pseudolinear estimator (BCSWPLE). The instrumental variable (IV) method is further introduced to solve the bias problem of the SWPLE, and the spherical weighted instrumental variables estimator (SWIVE) is proposed. The theoretical analysis shows that the SWIVE is asymptotically unbiased and achieves the Cramer-Rao lower bound (CRLB) when both the small Gaussian noise assumption and the first-order approximation are satisfied and the number of measurements is sufficiently large. The proposed algorithms can obtain quasi-closed-form solutions to the source location. Therefore, they can avoid convergence problems that are common in the maximum likelihood estimator (MLE) and achieve more robust performance. Moreover, the proposed algorithms have lower computational complexities than traditional algorithms. When there are sufficient measurements, two bias mitigation algorithms can significantly suppress the bias, among which the SWIVE can achieve similar or even better bias performance compared with the MLEs. Extensive simulations prove the proposals of the study.

关键词： Location awareness Maximum likelihood estimation signal processing algorithms Azimuth Position measurement Noise measurement Jacobian matrices Angle-of-arrival (AOA) bias compensation homogeneous least square instrumental variables pseudolinear estimator spherical source localization

来源：评论

学校读者我要写书评

暂无评论

Mixed Gas Detection and Temperature Compensation Based on Photoacoustic Spectroscopy

IEEE PHOTONICS JOURNAL

引用

IEEE PHOTONICS JOURNAL 2024年第2期16卷 1页

作者： Sun, Chao Hu, Runze Liu, Niansong Ding, Jianjun Jianghan Univ Wuhan 430014 Peoples R China

In recent years, with the continuous progress of technology and the development of society, the demand for updating trace gas detection technology has been increasing. The ability to quickly and accurately detect the composition and concentration of gases has become a hot topic in current research. In response to address issues such as difficulties in judging data for classification and recognizing gas components with low accuracy, a KNN-SVM algorithm has been proposed. The algorithm primarily reclassifies ambiguous data that are close to the hyperplane but do not have a clear affiliation, capturing data characteristics more comprehensively. It determines the weight ratio of each algorithm through experiments to improve the accuracy of gas category discrimination. Experimental results show that, compared to the traditional SVM algorithm, the KNN-SVM algorithm performs better in gas classification prediction, with an accuracy rate of 99.167% and an AUC indicator of 99.375%, enhancing the accuracy of gas detection. In response to the impact of temperature on the system during the experimental process, a WOA-BP temperature compensation model was established to compensate for temperature in gas concentration detection. After comparing various optimized BP neural network models, the performance of the WOA-BP temperature compensation was the most outstanding, with an R2 of 97.89%, MAE of 1.4868, RMSE of 2.0416, and a convergence speed after 15 iterations, reducing detection errors and thus achieving precise detection of low-concentration mixed gases.

关键词： Classification algorithms Support vector machines Gases Prediction algorithms Vectors signal processing algorithms Predictive models Photoacoustic spectroscopy gas detection KNN-SVM temperature compensation WOA-BP

来源：评论

学校读者我要写书评

暂无评论

An Invitation to Hypercomplex Phase Retrieval: Theory and applications

引用

IEEE signal processing MAGAZINE 2024年第3期41卷 22-32页

作者： Jacome, Roman Mishra, Kumar Vijay Sadler, Brian M. Arguello, Henry Univ Ind Santander Bucaramanga 680002 Colombia US DEVCOM Army Res Lab Adelphi MD 20783 USA Univ Ind Santander Syst Engn Dept Bucaramanga 680002 Santander Colombia

Hypercomplex signal processing (HSP) provides state-of-the-art tools to handle multidimensional signals by harnessing the intrinsic correlation of the signal dimensions through Clifford algebra. Recently, the hypercomplex representation of the phase retrieval (PR) problem, wherein a complex-valued signal is estimated through its intensity-only projections, has attracted significant interest. The hypercomplex PR (HPR) arises in many optical imaging and computational sensing applications that usually comprise quaternion- and octonion-valued signals. Analogous to the traditional PR, measurements in HPR may involve complex, hypercomplex, Fourier, and other sensing matrices. This set of problems opens opportunities for developing novel HSP tools and algorithms. This article provides a synopsis of the emerging areas and applications of HPR with a focus on optical imaging.

关键词： Correlation Algebra Image processing signal processing algorithms Optical imaging Sensors Hypercomplex Mathematics Multidimensional signal processing

来源：评论

学校读者我要写书评

暂无评论

Simpler Gradient Methods for Blind Super-Resolution With Lower Iteration Complexity

引用

IEEE TRANSACTIONS ON signal processing 2024年 72卷 5123-5139页

作者： Li, Jinsheng Cui, Wei Zhang, Xu Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Xidian Univ Sch Artificial Intelligence Key Lab Collaborat Intelligence Syst Minist Educ Xian 710126 Peoples R China Xidian Univ Sch Artificial Intelligence Key Lab Intelligent Percept & Image Understanding Minist Educ Xian 710126 Peoples R China

We study the problem of blind super-resolution, which can be formulated as a low-rank matrix recovery problem via vectorized Hankel lift (VHL). The previous gradient descent method based on VHL named PGD-VHL relies on additional regularization such as the projection and balancing penalty, exhibiting a suboptimal iteration complexity. In this paper, we propose a simpler unconstrained optimization problem without the above two types of regularization and develop two new and provable gradient methods named VGD-VHL and ScalGD-VHL. A novel and sharp analysis is provided for the theoretical guarantees of our algorithms, which demonstrates that our methods offer lower iteration complexity than PGD-VHL. In addition, ScalGD-VHL has the lowest iteration complexity while being independent of the condition number. Furthermore, our novel analysis reveals that the blind super-resolution problem is less incoherence-demanding, thereby eliminating the necessity for incoherent projections to achieve linear convergence. Empirical results illustrate that our methods exhibit superior computational efficiency while achieving comparable recovery performance to prior arts.

关键词： Superresolution Complexity theory Convergence Minimization Gradient methods signal processing algorithms Sensors Optimization Vectors Radar imaging Blind super-resolution vanilla gradient descent scaled gradient descent low-rank matrix factorization

来源：评论

学校读者我要写书评

暂无评论

A New Diffusion Filtered-X Affine Projection Algorithm: Performance Analysis and Application in Windy Environment

引用

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE processing 2024年 32卷 1596-1608页

作者： Chu, Yijing Zhao, Sipei Niu, Feng Dong, Yongzheng Zhao, Yuezhe South China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou 510640 Peoples R China Univ Technol Sydney Fac Engn & IT Ctr Audio Acoust & Vibrat Ultimo NSW 2007 Australia Natl Inst Metrol Div Mech & Acoust Beijing 100029 Peoples R China Beijing Xiaomi Mobile Software Co Ltd Beijing 100085 Peoples R China

Wind noise caused by turbulent flows over microphones usually has detrimental impacts on the reference signal of an active noise control (ANC) system and degrade its performance considerably. This paper evaluates the influence of wind noise on the filtered-x affine projection algorithm (FxAPA) for ANC systems. To improve the performance of noise control systems in windy environments, the FxAPA is modified based on a wind-noise-free least mean squares error and the diffusion control technology that could suppress interruptions in the collected primary noise. Performance analysis of the resulting de- regularized diffusion FxAPA (Diff-FxAPA) algorithm has been carried out at the presence of wind noise, which reveals the underlying mechanism of the new algorithm on suppressing the wind noise interruption. Difference equations describing the mean and mean squares convergence behaviors of this ANC system are derived to characterize its optimal solution, estimation bias and variance, and convergence conditions. Computer simulations with real-recorded data validate the theoretical analysis and show that the noise reduction performance of conventional ANC methods degrades with wind noise while the proposed algorithm has a stable performance under a variety of windy conditions.

关键词： Microphones Wind signal processing algorithms Acoustics Loudspeakers Noise reduction Convergence Affine projection algorithm (APA) and performance analysis diffusion active noise control (ANC) wind noise

来源：评论

学校读者我要写书评

暂无评论

Robust and Unambiguous Four-Channel Monopulse Two-Target Resolution: A Polarimetric Closed-Form Approach

引用

IEEE TRANSACTIONS ON signal processing 2024年 72卷 4222-4236页

作者： Liu, Yibin Wang, Shengbin Luo Wu, Guoqing Wang, Ping Li, Yongzhen Natl Univ Def Technol State Key Lab Complex Electromagnet Environm Effec Changsha 410073 Peoples R China

Four-channel monopulse (FCM) technique is integral to contemporary radar systems for pinpointing and tracking multiple targets. However, the practical utility of FCM is significantly hindered by the issue of estimation failure, which arises from the specific relative phases and positions of the targets. In this paper, we introduce a polarimetric four-channel monopulse (PFCM) approach designed to deliver efficient, robust, and unambiguous resolution of two targets. Generally, PFCM adaptively modulates the null-polarization for each target. We begin by dissecting the limitations of the traditional method, utilizing the closed-form solution of FCM. Subsequently, we devise a novel closed-form solution that harnesses polarimetric adaptive nulling (PAN) technology to estimate the angles of the two targets under two distinct scenarios: the ideal condition and angular ambiguity. Under ideal conditions, estimation is conducted directly using the received signals. Incorporating polarization information mitigates the estimation results' sensitivity to relative phase. To counteract the challenges of PAN failure in angular ambiguity situations, the proposed PFCM adeptly resolves the two targets by reconstructing the four-channel signal, indicating its applicability across various relative target positions. Furthermore, we present a comprehensive performance analysis focusing on three critical aspects. As a result, two closely spaced targets can be resolved robustly and unambiguously with minimal complexity. Numerical simulations and experimental results are substantiated to validate the effectiveness of the proposed method.

关键词： Radar signal resolution Radar polarimetry Superresolution Closed-form solutions Radar tracking signal processing algorithms Polarimetric four-channel monopulse (PFCM) polarimetric adaptive nulling (PAN) two-target resolution closed-form

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：