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检索条件"主题词=Iterative algorithms"

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Analysis of Cross-Domain Message Passing for OTFS Transmissions

Analysis of Cross-Domain Message Passing for OTFS Transmissi...

引用

IEEE (first ITW conference of the year) Information Theory Workshop (ITW)

作者： Ruoxi Chong Shuangyang Li Zhiqiang Wei Michail Matthaiou Derrick Wing Kwan Ng Giuseppe Caire Centre for Wireless Innovation (CWI) Queen's University Belfast UK Faculty of Electrical Engineering and Computer Science Technical University of Berlin Germany School of Mathematics and Statistics Xi'an Jiaotong University P. R. China School of Electrical Engineering and Telecommunications University of New South Wales Australia

ISBN: (数字)9798350348934

ISBN: (纸本)9798350348941

In this paper, we investigate the performance of the cross-domain iterative detection (CDID) framework with orthogonal time frequency space (OTFS) modulation, where two distinct CDID algorithms are presented. The proposed schemes estimate/detect the information symbols iteratively across the frequency domain and the delay-Doppler (DD) domain via passing either the a posteriori or extrinsic information. Building upon this framework, we investigate the error performance by considering the bias evolution and state evolution. Furthermore, we discuss their error performance in convergence and the DD domain error state lower bounds in each iteration. Specifically, we demonstrate that in convergence, the ultimate error performance of the CDID passing the a posteriori information can be characterized by two potential convergence points. In contrast, the ultimate error performance of the CDID passing the extrinsic information has only one convergence point, which, interestingly, aligns with the matched filter bound. Our numerical results confirm our analytical findings and unveil the promising error performance achieved by the proposed designs.

关键词： Time-frequency analysis Matched filters Lower bound System performance Simulation Message passing Modulation Symbols iterative algorithms Convergence

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Joint Communication and Computing Optimization for Digital Twin Synchronization with Aerial Relay

Joint Communication and Computing Optimization for Digital T...

引用

IEEE International Conference on Communications (ICC)

作者： Yi Wang Markus Krantzik Lin Xiang l Anja Klein Engineering Lab Technische Universität Darmstadt Germany

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Digital twin (DT) applications usually need to be synchronized in real time with the state of the physical system (PS). This process includes both synchronizing the data collected by sensors in the PS to a server and updating the DT at the server in adaptation to the dynamics of the PS. However, communicating with power- and rate-limited sensors and processing high-volume sensed data with limited computing resources present significant challenges for DT synchronization. In this paper, we tackle both bottlenecks by proposing a joint communication and computing design for DT synchronization. In particular, we exploit buffering at an aerial cluster head of the sensors and enable buffer-aided (BA) relaying to increase the communication throughput of the sensors during data synchronization. Moreover, we adopt a novel stream computing scheme, which allows for DT updating in parallel with data synchronization, to accelerate DT synchronization. To maximize the performance of the proposed approach, we jointly optimize the trajectory of the aerial relay and the communication and computing resource allocation for minimizing the DT synchronization time. The formulated problem is a mixed-integer nonconvex problem, which is generally intractable. To tackle this challenge, we propose a low-complexity two-layer iterative suboptimal algorithm. Our simulation results show that the DT synchronization time can be significantly reduced by up to 43.8%, through stream computing and the joint optimization of the relay's trajectory and the communication/computing resource allocation.

关键词： Simulation iterative algorithms Sensors Trajectory Digital twins Synchronization Resource management

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Distributed Nonlinear Model Predictive Control of Heterogeneous Battery Storage Systems

Distributed Nonlinear Model Predictive Control of Heterogene...

引用

Annual Conference of Industrial Electronics Society

作者： Filip Vrbanc Mateja Car Mario Vašak Vinko Lešić Laboratory for Renewable Energy Systems University of Zagreb Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

This paper deals with distributed control of variable efficiency heterogeneous battery storage systems connected in a microgrid. The nonlinear efficiency of battery charging is taken from converters’ datasheet and identified battery internal resistance, and a corresponding nonlinear model is derived dependent on state of energy. Individual battery control, as a local nonlinear problem, is solved by using a sequential linear program. Distributed control with the central supervisor is then used to coordinate individual batteries within the storage system and ensure improved overall system operation while respecting the joint constraint of the grid connection power capacity. Asymmetric projection algorithm is used for distributed control, based on iterative convergence of individual battery control actions towards the optimal operation of the whole system. The algorithm is implemented in a realistic simulation scenario of six different batteries with their corresponding characteristics, real electricity prices and measured load consumption. Presented results show that distributed control satisfies global constraint, while obtaining better cost than the decentralized approach with previously reported 7% of increased savings of nonlinear over constant efficiency.

关键词： Resistance Costs Systems operation Decentralized control Optimal control Microgrids iterative algorithms Batteries Projection algorithms Convergence

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High-Performance Eigensolver Combining EigenExa and iterative Refinement

High-Performance Eigensolver Combining EigenExa and Iterativ...

引用

High Performance Computing, Networking, Storage and Analysis, SC-W: Workshops of the International Conference for

作者： Yuki Uchino Toshiyuki Imamura RIKEN Center for Computational Science Kobe Hyogo Japan

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

This study proposes a high-performance and reliable eigensolver via mixed-precision arithmetic between ordinary and highly-accurate precisions. Eigenvalue decomposition is ubiquitous in simulations. Various eigensolvers for computing approximations have been developed thus far. If eigenvalues are narrowly clustered, the computation of eigenvectors may be ill-posed. Thus, the computed eigenpairs may not be sufficiently accurate and lack reliability. In this study, we introduce mixed-precision iterative refinement methods to improve the accuracy of eigenvectors obtained using numerical methods. This approach contributes to obtaining sufficiently accurate results without arbitrary precision eigensolvers. We construct a high-performance and reliable eigensolver by combining the iterative refinement methods and EigenExa, a modern high-performance solver for large-scale and highly parallel computations. Numerical experiment results demonstrate the accuracy of the results and performance benchmark of the proposed approach.

关键词： Accuracy Error analysis Scalability High performance computing Conferences Approximation algorithms iterative algorithms Eigenvalues and eigenfunctions Supercomputers Reliability

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Hyperspectral Super-Resolution Using Nonlinear Unmixing and Nonnegative Tensor Factorization

Hyperspectral Super-Resolution Using Nonlinear Unmixing and ...

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International Conference on Information Fusion

作者： Qingke Zou Jie Zhou College of Mathematics Sichuan University Chengdu Sichuan China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

Fusing a hyperspectral image (HSI) and a multispectral image (MSI) to generate a super-resolution image (SRI) with refined spatial and spectral resolution is a popular technique in hyperspectral super-resolution (HSR). Most HSR methods accomplish this task by matrix or tensor decomposition in the framework of linear unmixing. Although these methods are effective to some extent, serious challenges remain. In this work, the linear unmixing is extended to nonlinear unmixing framework and a novel HSR method based on a generalized bilinear unmixing model in tensor format is proposed. Apart from the linear part, it additionally considers bilinear interactions between endmembers. A low-rank prior is incorporated into the abundance maps and nonlinear interaction abundance maps, which can adequately model non-local similarities in images. In addition, the total variance is used to explore the local spatial relationships of the image. The optimization is implemented using the alternating direction method of multipliers (ADMM) algorithm with analytical expressions for each iterative update step, which is difficult to implement even for algorithms that focus on nonlinear unmixing. The proposed method overcomes the inherent linear limitations of the linear unmixing framework and avoids the information loss caused by matrixing the HSI and MSI with 3D-structure. The experimental results of simulations on real hyperspectral datasets demonstrate the superiority of the proposed approach over the compared HSR methods.

关键词： Tensors Superresolution Convex functions iterative algorithms Computational efficiency Matrix decomposition Spatial resolution Optimization Image reconstruction Hyperspectral imaging

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Fault Diagnosis of Hyperbolic Distributed Parameter System

Fault Diagnosis of Hyperbolic Distributed Parameter System

引用

Data Driven Control and Learning Systems (DDCLS)

作者： Yu Song Jianxiang Zhang Institute of Intelligent Systems and Control Guangxi University of Science and Technology School of Automation Liuzhou P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

The problem of iterative learning control for hyperbolic distributed parameter systems with faults under sensor/actuator networks is studied. Many results have been achieved in previous studies on iterative learning control, but the problem of fault diagnosis for partial differential systems has rarely been mentioned. Therefore, this paper considers for the first time the occurrence of faults in a class of hyperbolic distributed-parameter systems with fluctuation equations having Kelvin-Voigt damping and viscous damping, and gives the corresponding fault estimation algorithms. An iterative learning based fault diagnosis algorithm and fault estimator are constructed in the article. The convergence of nonlinear system faults in sensor/actuator networks is demonstrated using the principle of compressive mapping. The convergence conditions for the convergence of virtual faults to real faults are obtained through rigorous mathematical analysis. Finally, numerical simulations are carried out according to the convergence conditions, and the numerical simulation results verify the effectiveness of the fault diagnosis algorithm designed in this paper.

关键词： Fault diagnosis Damping Numerical simulation iterative algorithms Sensor systems Sensors Distributed parameter systems

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E-Commerce Recommendation Algorithm Based on Data Augmentation and Attention Mechanism

E-Commerce Recommendation Algorithm Based on Data Augmentati...

引用

Emerging Technology (INCET), International Conference for

作者： Kun Peng Shandong Institute of Commerce and Technology Jinan Shandong China

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

Aiming at the limitations of traditional digital mining algorithms in the research of e-commerce recommendation algorithms, a recommendation algorithm research scheme based on data augmentation and attention mechanism was proposed. Firstly, the influencing factors is accurately located through iterative statistical theory, and the indicators is reasonably divided to reduce interference, and the data augmentation and attention mechanism is used to construct a recommendation algorithm research scheme. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional digital mining algorithm in terms of the research accuracy of the recommendation algorithm and the processing time of influencing factors, and has obvious advantages. The research of recommendation algorithm plays an extremely important role in the era of intelligent e-commerce, which can accurately predict and optimize the growth characteristics and product generation in the era of intelligent e-commerce. However, traditional digital mining algorithms have certain limitations in solving the simulation problem of e-commerce recommendation, especially when dealing with complex problems. In this paper, this paper proposes a recommendation algorithm based on data augmentation and attention mechanism to better solve this problem. The scheme accurately locates the influencing factors through iterative statistical theory, so as to determine the division of indicators, and uses data augmentation and attention mechanism to construct the scheme. Experimental results show that under certain evaluation criteria, the accuracy and speed of the scheme is significantly improved for different problems, and it has better performance. Therefore, the simulation scheme based on data augmentation and attention mechanism can better solve the limitations of traditional digital mining algorithms and improve the accuracy and efficiency of simulation in the research of e-commerce r

关键词： Attention mechanisms Accuracy Key performance indicator Data augmentation Prediction algorithms iterative algorithms Electronic commerce

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A Fast iterative Airborne STAP for Coprime Sampling Structure

A Fast Iterative Airborne STAP for Coprime Sampling Structur...

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International Conference on Information, Communication and Networks (ICICN)

作者： Mingfu Li Hui Li School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu P. R. China Chengdu Textile College Chengdu P. R. China

ISBN: (数字)9798350355802

ISBN: (纸本)9798350355819

In the space-time adaptive processing (STAP) algorithm, the coprime structure can achieve better clutter suppression performance at lower hardware costs compared to the uniform linear structure. However, in practical scenarios, the performance of the algorithm is limited by the number of training samples. Therefore, this paper proposes a fast iterative heterogeneous STAP algorithm. To effectively estimate the clutter covariance matrix (CCM) and ensure its low rank, truncated nuclear norm regularization technique is introduced, which converts the non-convex problem into a convex optimization problem. Then, the virtual CCM is solved through a two-step iterative algorithm. The effectiveness and accuracy of the proposed algorithm are verified through simulation experiments.

关键词： Training Heuristic algorithms Estimation Sensor phenomena and characterization Minimization Convex functions iterative algorithms Covariance matrices Clutter Kernel

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Recursive and Nonrecursive Passive Target Localization algorithms with Bearing-Only Measurements

Recursive and Nonrecursive Passive Target Localization Algor...

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Ocean Studies (ICOS), International Conference on

作者： O.A. Stepanov V.P. Zolotarevich M.S. Ivanov A.V. Motorin ITMO University Concern CSRI Elektropribor JSC St. Petersburg Russia

ISBN: (数字)9798331532307

ISBN: (纸本)9798331532314

The paper investigates the problem of passive target localization from a moving observer using bearing-only measurements. The following three estimation algorithms are considered: a recursive iterative extended Kalman smoother; a nonrecursive iterative batch linearized filter, and a recursive iterative batch linearized smoother. The accuracy and computational complexity of the recursive and nonrecursive algorithms are compared using the Monte Carlo simulation. The Cramer-Rao lower bound for the problem under consideration is calculated. The advantages of the recursive iterative batch linearized smoother over the nonrecursive iterative batch linearized filter and the recursive iterative extended Kalman smoother are shown.

关键词： Location awareness Accuracy Software algorithms Estimation Sea measurements Filtering algorithms Observers iterative algorithms Trajectory Kalman filters

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Optimal Resource Allocation Design for Wideband ISAC Systems with Discrete True-Time Delayers

Optimal Resource Allocation Design for Wideband ISAC Systems...

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IEEE Conference on Wireless Communications and Networking

作者： Wenhao Wang Deli Qiao Lei Yang Yueying Zhan Derrick Wing Kwan Ng School of Communication and Electronic Engineering East China Normal University Shanghai China Technology and Engineering Center for Space Utilization Chinese Academy of Sciences China University of New South Wales Australia

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

This paper investigates resource allocation design for wideband integrated sensing and communication (ISAC) systems. We aim to minimize the Cramér-Rao Bound (CRB) for target estimation by jointly optimizing subcarrier allocation, digital beamforming matrices, and frequency-independent and frequency-dependent analog beamforming matrices at the base station (BS) adopting a hybrid beamforming structure. We formulate the optimization design as a non-convex mixed-integer nonlinear programming (MINLP) problem, subject to the transmit power budget constraint of the BS, the rate quality-of-service (QoS) constraints for users, and the discrete nature of the analog beamformer. To achieve a globally optimal solution for the complicated design problem, an iterative resource allocation algorithm is proposed by exploiting the generalized Bender's decomposition (GBD) method. Our simulation results demonstrate the crucial importance of simultaneously optimizing all available degrees-of-freedom (DoFs) in wideband ISAC systems jointly and optimally. Besides, our results unveil that deploying true-time-delayer (TTD) units with limited bit-resolution time delays can achieve substantial gains in both communication and sensing performances.

关键词： Array signal processing Simulation Quality of service Integrated sensing and communication iterative algorithms Frequency estimation Resource management Wideband Optimization Radio spectrum management

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