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检索条件"主题词=Iterative algorithms"

共 16604 条记录，以下是431-440 订阅

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Simple Randomized Cur algorithms for Method of Moments Matrix Compression

Simple Randomized Cur Algorithms for Method of Moments Matri...

引用

International Conference on Electromagnetics in Advanced Applications (ICEAA)

作者： Juan M. Rius Alexander Heldring Eduard Ubeda Universitat Politècnica de Catalunya (UPC)

ISBN: (数字)9798350360974

ISBN: (纸本)9798350360981

The Method of Moments (MoM) discretization of electromagnetic scattering problems modeled with Integral Equations [1] results in systems of equations with a vast number of unknowns, demanding significant computational resources. Over the past three decades, substantial research has produced highly efficient algorithms [2], termed “Fast Solvers”, with reduced storage requirements and computational complexity, enabling iterative solutions on personal computers with millions of unknowns and even billions on supercomputers.

关键词： Computational modeling Integral equations Electromagnetic scattering Microcomputers Mathematical models Supercomputers iterative algorithms Electromagnetics Computational complexity Method of moments

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Efficient Design for NOMA Enabled Integrated Sensing and Semantic Communication

Efficient Design for NOMA Enabled Integrated Sensing and Sem...

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IEEE Conference on Vehicular Technology (VTC)

作者： Zhouxiang Zhao Yating Tang Yuzhi Yang Yuanyuan Dong Lexi Xu Zhaohui Yang Zhaoyang Zhang College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Zhejiang Provincial Key Laboratory of Info. Proc. Commun. & Netw. (IPCAN) Hangzhou China Research Institute China United Network Communications Corporation Beijing China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

This paper investigates semantic energy efficiency in a non-orthogonal multiple access (NOMA) enabled integrated sensing and semantic communication (ISSC) system. The model involves the base station (BS) transmitting information to multiple users while performing target sensing using dedicated beamforming. In the considered model, the BS needs to transmit substantial text data to each user using text semantic communication techniques while sensing the targets with certain constraints. Our goal is to maximize semantic energy efficiency and meet semantic communication and sensing accuracy requirements. We formulate an optimization problem for the beamforming matrix and semantic parameter, employing the Dinkelbach's algorithm for simplification and proposing an iterative solution. Numerical results validate the efficacy of the NOMA-ISSC scheme.

关键词： NOMA Vehicular and wireless technologies Array signal processing Semantics Energy efficiency iterative algorithms Data models

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A Digital Foreground Calibration Method for Pipeline SAR ADCs Using Extended Kalman Filter

A Digital Foreground Calibration Method for Pipeline SAR ADC...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Dayan Zhou Yuguo Xiang Junyan Ren Fan Ye State-Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China

ISBN: (数字)9798350361834

ISBN: (纸本)9798350361841

This article presents a digital foreground calibration algorithm based on sinewave fitting to mitigate mismatches and nonlinearities in analog-to-digital converters (ADCs). The ground truth of ADCs is obtained through sinewave fitting, and the weights in the ADCs output code reconstruction block are modified by the Least Mean Square (LMS) algorithm. An Extended Kalman Filter (EKF) is employed in sinefit block to reduce hardware complexity and facilitate iterative calculation. A modeling 12-bit pipeline successive-approximation-register (SAR) ADC is used to verify the performance of proposed calibration scheme. The simulation results show that SFDR and SNDR are improved by 32.3 dB and 19.2 dB after calibration, respectively.

关键词： Integrated circuit technology Simulation Pipelines Fitting Filtering algorithms iterative algorithms Hardware Calibration Kalman filters Analog-digital conversion

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Multiple Greedy Quasi-Newton Methods for Saddle Point Problems

Multiple Greedy Quasi-Newton Methods for Saddle Point Proble...

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Data-driven Optimization of Complex Systems (DOCS), International Conference on

作者： Minheng Xiao Shi Bo Zhizhong Wu Dept. Integrated System Engineering Ohio State University Columbus USA Dept. Mathematics and Statistics Boston University Boston USA College of Engineering UC Berkeley Berkeley USA

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

This paper introduces the Multiple Greedy Quasi-Newton (MGSR1-SP) method, a novel approach to solving strongly-convex-strongly-concave (SCSC) saddle point problems. Our method enhances the approximation of the squared indefinite Hessian matrix inherent in these problems, significantly improving both stability and efficiency through iterative greedy updates. We provide a thorough theoretical analysis of MGSR1-SP, demonstrating its linear-quadratic convergence rate. Numerical experiments conducted on AUC maximization and adversarial debiasing problems, compared with state-of-the-art algorithms, underscore our method's enhanced convergence rate. These results affirm the potential of MGSR1-SP to improve performance across a broad spectrum of machine learning applications where efficient and accurate Hessian approximations are crucial.

关键词： Machine learning algorithms Accuracy Estimation Machine learning Approximation algorithms Stability analysis iterative algorithms Optimization Numerical stability Convergence

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Design of OMNET++ for Input-queued switching Networks

Design of OMNET++ for Input-queued switching Networks

引用

Computer Engineering and Intelligent Communications (ISCEIC), International Symposium on

作者： Bowen Cheng Weibin Zhou School of Electronic Information and Automation Tianjin University of Science and Technology Tianjin China

ISBN: (数字)9798331518677

ISBN: (纸本)9798331518684

To evaluate the performance of iterative scheduling algorithms in input queuing and switching networks, this study constructs a specialized simulation platform using OMNET++ software suit. Adopted through a modular and object-oriented approach, the platform supports various scheduling algorithms and can accurately simulate the complete process from data generation to output, including the processing of different types of service flows. By implementing the iSLIP, DRRM, EiSLIP and EDRRM algorithms, the platform's network-level performance simulation capability is verified under different load conditions, demonstrating its potential in promoting the research of network architecture optimization and scheduling strategies, which is of great significance in promoting the theoretical and practical advancement of network technology. This platform fills the gap of existing simulation software in specific areas and provides an effective tool for the research of iterative scheduling algorithms.

关键词： Scheduling algorithms Software algorithms Switches Network architecture Data collection iterative algorithms Software Scheduling Optimization

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Sparse Channel Estimation for M-QAM-Based Underwater Acoustic Communication Systems

Sparse Channel Estimation for M-QAM-Based Underwater Acousti...

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International Conference on Computer Science and Engineering (UBMK)

作者： Mhd Tahssin Altabbaa Berkay Tekat Emin Tarik Iseri Electrical and Electronics Engineering Istanbul Yeni Yuzyil University Istanbul Turkiye

ISBN: (数字)9798350365887

ISBN: (纸本)9798350365894

This paper investigates the channel estimation problem for M-QAM based underwater acoustic systems with Rayleigh fading. Utilizing the maximum a posteriori probability, the iterative expectation maximization algorithm conducts estimation of the channel coefficients in the frequency domain. Taking into account the M-QAM signalling for any M. Finally, the estimated channel enters a refinement process using the direct Fourier transform for sparse channel taps estimation in the time domain. Simulation results were carried out for 32QAM signalling, and the mean square error and bit error rate showed robustness for different pilot spacings.

关键词： Maximum a posteriori estimation Simulation Channel estimation Estimation Rayleigh channels Mean square error methods Robustness iterative algorithms Underwater acoustics Time-domain analysis

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Construction of Equipment Installation and Fault Diagnosis System for Chemical Project Based on Ant Colony Optimization Algorithm

Construction of Equipment Installation and Fault Diagnosis S...

引用

Artificial Intelligence and Autonomous Robot Systems (AIARS), International Conference on

作者： Xiaolei Luo Fushun Vocational and Technical College Fushun Liaoning China

ISBN: (数字)9798350376173

ISBN: (纸本)9798350376180

Based on Ant Colony Optimization (ACO) algorithm, this paper studies equipment installation and fault diagnosis in chemical projects. Firstly, this paper puts forward an optimization method of equipment installation based on ACO algorithm, and finds the optimal equipment layout scheme through iterative search to reduce installation cost and path length. The experimental results show that this method can effectively improve the efficiency and economy of equipment installation. Secondly, this paper discusses the application of ACO algorithm in the construction of fault diagnosis system for chemical projects. By combining the fault diagnosis model and ACO algorithm, the rapid diagnosis and location of equipment faults are realized. In this paper, a system framework considering equipment installation optimization and fault diagnosis is proposed, which provides a comprehensive solution for chemical project management. This research provides new ideas and methods for chemical project management, which has important theoretical and practical significance.

关键词： Fault diagnosis Performance evaluation Ant colony optimization Costs Project management Simulated annealing iterative algorithms Safety Chemicals Convergence

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A Residual Graph Convolutional Network Algorithm Based on Unfolded WMMSE for Power Allocation

A Residual Graph Convolutional Network Algorithm Based on Un...

引用

Smart World Congress (SWC), IEEE

作者： Jinhong Yang Chunwei Miao Jian Zhang School of Computer Science and Engineering Central South University Changsha Hunan China

ISBN: (数字)9798331520861

ISBN: (纸本)9798331520878

Optimal power allocation is pivotal for enhancing network capacity and performance in wireless networks. To tackle the challenges posed by the high computational complexity of traditional algorithms and the limited interpretability and generalization of deep learning-based methods, inspired by the principles of deep unfolding and graph neural networks (GNNs), we propose a novel weighted minimum mean square error (WMMSE) unfolding-based residual graph convolutional network architecture (UWMMSE-RGCN). Specifically, our method unfolds the WMMSE algorithm, maintaining the iterative structure of WMMSE, and utilize GNNs to learn the key iterative variables of WMMSE to approximate the complex computational steps of the iterative variables. The methodology aims to capitalize on domain knowledge while achieve exceptional performance and computational efficiency. Additionally, we have developed a residual graph convolutional network (RGCN) by integrating residual connection into the GNNs. This design promotes the integration of features across diverse neighborhood scopes of nodes, thereby bolstering the architecture’s generalization performance. Theoretical analysis confirms the permutation equivariance of our method, which ensures its generalization to different network topologies. Experiments validate that the proposed unfolded architecture surpasses other deep unfolding algorithms in terms of performance and generalization. It demonstrates potential for scalability to larger network sizes and adaptability to diverse channel conditions.

关键词： Graph convolutional networks Network topology Wireless networks Scalability Computer architecture iterative algorithms Computational efficiency Topology Resource management Mobile ad hoc networks

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A High-Precision Edge Detection Algorithm Based on Improved Sobel Operator-Assisted HED

A High-Precision Edge Detection Algorithm Based on Improved ...

引用

IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Yeborui Yuan Wenyuan Chen Jie Tang Jia Yang School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China State Key Laboratory of Robotics Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In response to the problem of poor detection performance of the traditional Sobel operator in edge detection, a high-precision edge detection algorithm based on Sobel operator-assisted Holistically-nested Edge Detection (HED) network was proposed, which is named ISAHED here. The algorithm is designed as follows. Firstly, an improved Sobel operator based on the traditional Sobel operator was proposed through adding gradient direction. Then, the image output by the improved Sobel operator is taken as the ground-truth image and as the end-to-end comparison object in a HED-like network. Finally, the ISAHED algorithm outputs edge images with better quality through iterative learning of the HED-like neural network. The experimental results prove that the proposed ISAHED algorithm has better edge detection performance by visually observing the final edge images and further evaluating the values of FOM. This work provides an important reference for the further development of the edge detection technology.

关键词： Automation Image edge detection Image processing Neural networks Control systems iterative algorithms Intelligent systems

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Fast Simulation of Antenna Array with Parameters Variation

Fast Simulation of Antenna Array with Parameters Variation

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IEEE International Conference on Computational Electromagnetics (ICCEM)

作者： Xingkai Cheng Hanru Shao Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China

ISBN: (数字)9798350383317

ISBN: (纸本)9798350383324

In this work, we propose a hybrid method to fast solve the optimization of array located on the PEC carrier inside the dielectric radome with parameters variation. By constructing a reusable low-rank reduced-order model (ROM) for complex carriers, a large number of repeated calculations are reduced and the analysis cost of the antenna array is reduced when the position of array is modified. By combining of frequency-and material-independent response (FMIR), the sweep of media parameters and frequency can be accelerated. The tangential equivalence principle algorithm (T -EPA) is applied to solve the array problem, and the number of unknowns on the antenna array is transferred to the equivalent surface, which is easier for the iterative convergence of the matrix equation. Therefore, the number of unknowns and the analysis cost of the antenna array can be reducecd.

关键词： Costs Media Reduced order systems Mathematical models iterative algorithms Radomes Electromagnetics

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