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检索条件"主题词=Iterative algorithms"

共 16765 条记录，以下是501-510 订阅

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Real-Time Phase Retrieval Using On-the-Fly Training of Sample-Specific Surrogate Models

Real-Time Phase Retrieval Using On-the-Fly Training of Sampl...

引用

International Symposium on Computing and Networking (CANDAR)

作者： Ryota Koda Keichi Takahashi Hiroyuki Takizawa Nozomu Ishiguro Yukio Takahashi Tohoku University Sendai Japan

ISBN: (数字)9798331528362

ISBN: (纸本)9798331528379

Abstract—Recently, X-ray ptychography is attracting attention as a non-destructive imaging method with high spatial resolution. X-ray ptychography reconstructs a sample image by performing iterative phase retrieval from its diffraction patterns. However, iterative phase retrieval is time-consuming, and thus real-time reconstruction is challenging. One approach to accelerating phase retrieval uses a deep learning based surrogate model to predict the sample. By performing iterative phase retrieval using the model predictions as initial estimates, it is possible to achieve faster reconstruction compared to conventional iterative phase retrieval algorithms. However, although these methods assume to train a surrogate model for individual cases, the training time is often ignored in discussions on performance. Thus, conventional iterative methods might rather be faster if the training time is considered. The objective of this study is to implement real-time phase retrieval using surrogate models, including model training and prediction times. For this purpose, we propose a method to create a sample-specific surrogate model on-the-fly from a subset of observed data and to perform iterative phase retrieval using the predictions of the model. The proposed method is up to 2.8 times faster than conventional iterative phase retrieval, including training dataset creation time and surrogate model training time. In addition, the proposed method also ensures that the reconstructed images are physically correct because it performs the phase retrieval from the surrogate model predictions. This result indicates that it is important to find a good trade-off point between model accuracy and model training time.

关键词： Training Computational modeling Predictive models X-ray diffraction Real-time systems iterative algorithms Data models Spatial resolution Image reconstruction X-ray imaging

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Spherical Projection Based Clustering Algorithm for Cooperative Sweep Coverage in Crowdsourcing

Spherical Projection Based Clustering Algorithm for Cooperat...

引用

IEEE International Conference on Web Services (ICWS)

作者： Yucen Gao Xikai Wei Hui Gao Qun Li Xiaofeng Gao Guihai Chen Department of Computer Science and Engineering MoE Key Lab of Artificial Intelligence Shanghai Jiao Tong University Shanghai China Didi Chuxing Technology Co. Beijing China

ISBN: (数字)9798350368550

ISBN: (纸本)9798350368567

The sweep coverage problem is one of the important issues in spatial crowdsourcing, which requires task participants to monitor a series of Points of Interest (PoIs) periodically. In this paper, we study the Cooperative Sweep Coverage (CSC) problem with the objective of minimizing the maximum sweep period. We propose an iterative clustering algorithm based on spherical projection, called SP-Cycle. The algorithm firstly projects the points in the 2D space to a spherical surface in the 3D space. It then utilizes a new balancing clustering algorithm and uses an iterative coordinate updating method in the 3D spherical space based on the gradient descent, the aim of which is to use the simple minimum spanning tree length computation in the spherical surface to replace the complex Traveling Salesman Problem (TSP) cycle computation in the original 2D space, which improves the performance while keeping a low computational complexity. After we get the clusters, we can compute the lengths of TSP cycles and enter a new iteration. Experimental results based on synthetic and real-world datasets demonstrate the effectiveness of our proposed algorithm. The code is available at https://***/GaoYucen/CSC.

关键词： Crowdsourcing Three-dimensional displays Codes Web services Clustering algorithms Traveling salesman problems iterative algorithms Space exploration Computational complexity Monitoring

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Research on Application Technology of Expert Knowledge Graph Based on Greedy iterative Search Algorithm

Research on Application Technology of Expert Knowledge Graph...

引用

Artificial Intelligence and Electromechanical Automation (AIEA), International Conference on

作者： Wei Yang Weizheng Kong Yukun Song State Grid Energy Research Institute Co.Ltd Beijing China

ISBN: (数字)9798350366174

ISBN: (纸本)9798350366181

In this paper, an expert matching strategy based on greedy iterative search algorithm (GIS) is proposed to solve the problem of selecting experts for science and technology project review. GIS algorithm iteratively selects the most matched experts and gradually optimizes the combination of experts to achieve the best matching effect. This paper introduces the implementation steps of GIS algorithm in detail, and compares the performance of two greedy strategies and maximum flow matching strategies in terms of matching time and matching weight sum through experiments. The experimental results show that the greedy matching strategy is superior to the maximum flow matching strategy in both speed and effect.

关键词： Greedy algorithms Correlation Automation Reviews Knowledge graphs Search problems iterative algorithms Optimal matching Artificial intelligence

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iterative Detection Algorithm with LDPC Decoder in Cyclic-Prefix OTFS System

Iterative Detection Algorithm with LDPC Decoder in Cyclic-Pr...

引用

Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Mingfeng Zhang Jinhua Sun Xiaojun Wu Xidian University Chang’ an University

ISBN: (数字)9798350374513

ISBN: (纸本)9798350374520

Orthogonal time-frequency space (OTFS) uses symplectic finite Fourier transform (SFFT) to convert time-frequency doubly selective channel into sparse delay-Doppler channel, which can resist Doppler frequency shifts in high-mobility scenarios. For signal detection in the OTFS system, maximum-ratio combining (MRC) can be used to extract and coherently combine the received multipath components of the transmitted signal to improve the signal-to-noise ratio (SNR) of the combined signal. We describe the delay-Doppler input-output relation for two dimensional signal with ideal waveforms and its corresponding vectorized form for the cyclic prefix OTFS (CP-OTFS) system. Based on this relationship, the delay-Doppler domain MRC algorithm is first introduced to CP-OTFS system. And the MRC detector is further combined with low density parity check (LDPC) code as a turbo decision feedback equalizer (DFE) structure to detect signals, which can improve the detection performance of CP-OTFS system.

关键词： Time-frequency analysis Signal processing algorithms Detectors iterative algorithms Decision feedback equalizers Vectors Speech processing

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An optimized Tikhonov regularization algorithm for EIT image reconstruction

An optimized Tikhonov regularization algorithm for EIT image...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Zehao Li Hongwei Ren Bo Yan Jiaxiang Xu School of Automation and Electrical Engineering University of Jinan Jinan China

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

In the electrical impedance imaging (EIT) problem, aiming at the problem that the traditional Tikhonov regularization algorithm uses a single L2 norm as the regularization term, which leads to the over-smoothing of the solution and the unclear reconstruction of the image, this paper proposes an iterative Tikhonov algorithm (MLTR) with multiple regularization as the penalty term and logarithmic weight factor solving. At the same time, the regularization matrix is modified to improve the lack of prior information caused by the traditional use of the identity matrix as the regularization matrix. Finally, in order to reduce the corresponding time and computational complexity, the dimensionality of MLTR algorithm reconstruction is reduced. Compared with traditional Tikhonov algorithm and iterative algorithms such as Land Weber and conjugate gradient (CG), MLTR algorithm has obvious improvement in imaging clarity and boundary artifacts. The relative error RIE of reconstructed images is as low as 0.0564, and the imaging time is significantly shortened after dimensionality reduction.

关键词： Dimensionality reduction Electrical impedance tomography Imaging Big Data iterative algorithms Impedance Information technology Computational complexity Artificial intelligence Image reconstruction

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Deep unfolding based microwave imaging with spin-decoupled programmable metasurface

Deep unfolding based microwave imaging with spin-decoupled p...

引用

IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Fan Zhang Weike Feng Chaohui Wang Tong Liu Tao Pu Huanhuan Gao Zhengjie Wang He-Xiu Xu Air Force Engineering University Xi’an China

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

In this paper, the deep unfolding (DU) based microwave imaging method for near-field objects using 1-bit spin-decoupled programmable metasurface (SPM) is studied. First, a 1-bit SPM operating at 12 GHz is designed. Then, the theoretical imaging model is established using the plane-wave angular spectrum approach. Finally, the imaging methods based on the iterative shrinkage-thresholding algorithm (ISTA) and the learned ISTA are presented. By comparing the imaging results obtained by different methods, it is verified that the designed SPM equipped with the DU method is a promising technique for microwave imaging with excellent performance.

关键词： Microwave integrated circuits Artificial neural networks Microwave communication Metasurfaces iterative algorithms Information and communication technology Microwave FET integrated circuits

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

Recursive and Nonrecursive Passive Target Localization Algor...

引用

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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A Fast iterative Airborne STAP for Coprime Sampling Structure

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

引用

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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A Unified Tensor-Based Joint Communication and Sensing Parameter Estimation for ISAC with Large-Scale User Access

A Unified Tensor-Based Joint Communication and Sensing Param...

引用

Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Tiancheng Yang Dongxuan He Huazhou Hou Hua Wang Yongming Huang Zhaocheng Wang Tony Q.S. Quek School of Information and Electronics Beijing Institute of Technology Beijing China Pervasive Communication Research Centre Purple Mountain Laboratories Nanjing China School of Information Science and Engineering Southeast University Nanjing China Department of Electronic Engineering Tsinghua University Beijing China Information Systems Technology and Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

The combination of active user detection (AUD) and integrated sensing and communication (ISAC) can be utilized to realize communication and sensing functionalities over one hardware platform in the ultra-massive machine-type communications (umMTC). However, due to the received signals are typically coupled in both AUD and ISAC, it is hard to obtain the communication and sensing parameters. To solve this problem, the actual channel model is first converted into a unified form through CANDECOMP/PARAFAC decomposition (CPD) to mitigate the interference between communication and radar signals. Then, by utilizing the matrix subspace-based method, the factor matrices are accurately estimated, where the equivalent path parameters can be extracted. Furthermore, to estimate the coupled path parameters, an alternating iterative estimation algorithm is proposed. Simulation results verify the superiority of our proposed joint communication and sensing parameter estimation algorithm in AUD, channel estimation, and radar sensing.

关键词： Parameter estimation Simulation Estimation Channel estimation Radar Integrated sensing and communication iterative algorithms Radar signal processing Matrix decomposition Matrix converters

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Predictive Control Strategy for DC Microgrid Integrated EV Charging Stations in Oslo

Predictive Control Strategy for DC Microgrid Integrated EV C...

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Sustainable Energy and Future Electric Transportation (SEFET), International Conference on

作者： K. Raghavendra Naik Mohan lal Kolhe M. Krishna Siva Prasad Gibran David Agundis Juan C. Vasquez Josep M. Guerrero AAU Energy Department Aalborg University & Asst. prof in NIT Jamshedpur Aalborg Denmark Faculty of Engineering and Science University of Agder Kristiansand Norway Computer Science and Engineering Department SRM university AP. Guntur Andhra Pradesh AAU Energy Department Center for Research on Microgrids Aalborg University Aalborg Denmark

ISBN: (数字)9798350383997

ISBN: (纸本)9798350384000

Norway holds highest per capita Electric vehicle (EV) shares globally. To meet the recharge demand from such large EVs fleet, fast charging infrastructure is essential. But, the fast charging stations are unable to fulfill the charging request of EV owners due to restricted grid power supply. Peak shaving has partially addressed this issue with a solar PV-Battery energy storage system (BESS) integrated Microgrid (MG) configuration. But, maintaining the reliability and stability of Microgrid (MG) against intermittent EV arrivals during peak load of the grid is a critical objective. To address this issue a Micro hydro generator-Solar PV-BESS integrated DC MG with iterative predictive control (ITPC) algorithm is proposed in this paper. With the prediction of EV load arrivals on iteration basis, the proposed algorithm operates the Micro hydro generator in such a way that EV load is supplied under the peak load condition with optimal dependency on BESS. The performance of the proposed strategy evaluated against the real time EV load data of Oslo as a case study. The proposed strategy achieves 9.3% improved fall in DC-link voltage and 67.735% reduced depth of discharge of BESS.

关键词： Microgrids Prediction algorithms Electric vehicle charging Real-time systems iterative algorithms Discharges (electric) US Department of Defense Fast charging Voltage control Predictive control

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