检索结果-内蒙古大学图书馆

18th IEEE International Conference on Computer Science and Information Technologies, CSIT 2023

作者： Izonin, Ivan Tkachenko, Roman Shcherbii, Ostap Berezsky, Oleh Krak, Iurii Oliinyk, Maksym Lviv Polytechnic National University Department of Artificial Intelligence Lviv Ukraine Lviv Polytechnic National University Department of Publishing Information Technologies Lviv Ukraine West Ukrainian National University Department of Computer Engineering Ternopil Ukraine Taras Shevchenko National University of Kyiv Department of Theoretical Cybernetics Kyiv Ukraine

ISBN: (纸本)9798350360462

The accuracy of solving the approximation tasks in the case of analysis of large volumes of tabular biomedical datasets by machine learning methods is not always high. This is explained by the complex, non-linear dependencies inside a multi-parametric dataset of a large volume, which combines medical-biological and engineering-technical features. The task of increasing the accuracy of the machine learning algorithm, ANN, or a certain mathematical model, in particular for the case when they are a 'black box' during the intellectual analysis of such data, is urgent. The paper proposed a new two-step method for the refinement of regression model parameters (a direct approach). It is based on the principles of approximation by rational fractions, which have many advantages compared to other known methods. Simulation of the developed method is implemented as a cascade of two machine learning algorithms. Experimental studies were carried out based on SGD and extended-input SGTM neural-like structure using a real-world large biomedical dataset. We show a significant increase in the approximation accuracy of the designed method in comparison with several known methods, including cascades. © 2023 IEEE.

关键词： approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Policy Iteration Based Approximate Dynamic Programming Toward Autonomous Driving in Constrained Dynamic Environment

引用

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第5期24卷 5003-5013页

作者： Lin, Ziyu Ma, Jun Duan, Jingliang Li, Shengbo Eben Ma, Haitong Cheng, Bo Lee, Tong Heng Tsinghua Univ Sch Vehicle & Mobil Beijing 100084 Peoples R China Hong Kong Univ Sci & Technol Guangzhou Robot & Autonomous Syst Thrust Guangzhou Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Peoples R China Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 117583 Singapore

In the area of autonomous driving, it typically brings great difficulty in solving the motion planning problem since the vehicle model is nonlinear and the driving scenarios are complex. Particularly, most of the existing methods cannot be generalized to dynamically changing scenarios with varying surrounding vehicles. To address this problem, this development here investigates the framework of integrated decision and control. As part of the modules, static path planning determines the reference candidates ahead, and then the optimal path-tracking controller realizes the specific autonomous driving task. An innovative and effective constrained finite-horizon approximate dynamic programming (ADP) algorithm is herein presented to generate the desired control policy for effective path tracking. With the generalized policy neural network that maps from the state to the control input, the proposed algorithm preserves the high effectiveness for the motion planning problem towards changing driving environments with varying surrounding vehicles. Moreover, the algorithm attains the noteworthy advantage of alleviating the typically heavy computational loads with the mode of offline training and online execution. As a result of the utilization of multi-layer neural networks in conjunction with the actor-critic framework, the constrained ADP method is capable of handling complex and multidimensional scenarios. Finally, various simulations have been carried out to show that the constrained ADP algorithm is effective.

关键词： Planning Autonomous vehicles Vehicle dynamics Task analysis Heuristic algorithms approximation algorithms Roads Autonomous driving approximate dynamic programming motion planning constrained optimization reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Online Optimal Event-Triggered H∞ Control for Nonlinear Systems With Constrained State and Input

引用

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2023年第1期53卷 131-141页

作者： Song, Ruizhuo Liu, Lu Xia, Lina Lewis, Frank L. Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing Engn Res Ctr Ind Spectrum Imaging Beijing 100083 Peoples R China Univ Texas Arlington UTA Res Inst Ft Worth TX 76012 USA

Taking safety and performance into consideration, the state and control input of the actual engineering system are often constrained. For this kind of problem, this article puts forward an online dual event-triggered (ET) adaptive dynamic programming (ADP) optimal control algorithm for a class of nonlinear systems with constrained state and input. First, the original system is transformed into another system through the barrier function, after that, a suitable value function with a nonquadratic utility function is designed to obtain the optimal control pair. In addition, on the premise of the asymptotic stability of the system, the trigger condition is devised, and the intersampling time analysis is proved that the algorithm can avoid the Zeno phenomenon. What is more, the critic, action, and disturbance neural networks (NNs) are trained to approximate value function and control sequences, subsequently, the approximation error is proved to be uniformly ultimately boundedness (UUB). Finally, two comparative experiments based on the robot arm model are simulated to verify that the algorithm can make control policies update only when the system has the requirement and keep satisfactory control effect, which can effectively decrease the number of data transfers and reduce the calculation burden.

关键词： Optimal control Mathematical models Heuristic algorithms Dynamic programming Asymptotic stability approximation algorithms Safety Adaptive dynamic programming (ADP) constrained system event-triggered (ET) H∞ control

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis and Phase Shift Design of IRS-Aided Uplink OTFS-SCMA

引用

IEEE ACCESS 2023年 11卷 133059-133069页

作者： Li, Jiarui Hong, Yi Monash Univ Dept Elect & Comp Syst Engn Melbourne Vic 3800 Australia

In this paper, we consider an intelligent reflecting surface (IRS)-aided orthogonal time frequency space (OTFS)-based uplink sparse code multiple access (SCMA) communications system. We first conduct performance analysis in terms of pairwise error probability (PEP) and derive an upper bound on word error probability (WEP). According to this bound, we establish a system design criterion and propose two IRS phase shifts design algorithms using semidefinite relaxation (SDR) and gradient ascent (GA) methods. The computational complexity of these algorithms is discussed. Next, we derive an upper bound on the average bit error rate (BER) and investigate the system performance in terms of diversity and signal-to-noise (SNR) gains. Further, to recover transmitted information bits, we present a modified joint iterative Gaussian approximated message passing (MP) detection and SCMA decoding algorithm, enabling detection and SCMA demapping to occur in each iteration. Finally, simulation results demonstrate that our proposed IRS design algorithms achieve better error performance compared to the known approaches.

关键词： Manganese Uplink Delays approximation algorithms Time-frequency analysis Symbols Performance analysis Intelligent systems Phase shifters Intelligent reflecting surface (IRS) orthogonal time frequency space (OTFS) sparse code multiple access (SCMA) word error probability phase shifts design

来源：评论

学校读者我要写书评

暂无评论

A Novel Line approximation Approach for State Updates of Grid Maps 16th

A Novel Line Approximation Approach for State Updates of G...

引用

16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

作者： Niu, Jie Zhang, Dong Beijing University of Chemical Technology Beijing100029 China

ISBN: (纸本)9789819964826

Straight-line approximation algorithms are often used in state update processes of grid maps. They are primarily designed for drawing and displaying. Due to limitations of per-step’s single selection and sensors’ noise, historical obstacles may not be eliminated clearly on grid maps. To ensure the accuracy of robots’ environment modeling, we propose a cross-discrimination algorithm (CDA) for line approximation on grid maps. It introduces an optional extension to the single-selection strategy by considering the intersection coordinates of lines and grids. The incomplete removal problem is effectively addressed by incorporating these additional coordinate pairs for clearing, resulting in improved quality for downstream tasks. A series of experiments are conducted to assess the algorithm’s universality and robustness. The results of the experiments confirm the effectiveness of our algorithm in grid map processing. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Robust Interferometric ISAR Imaging With UAMP-Based Joint Sparse Signal Recovery

引用

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2023年第4期59卷 3890-3906页

作者： Kang, Hailong Li, Jun Guo, Qinghua Martorella, Marco Giusti, Elisa Cai, Jinjian Xidian Univ Hangzhou Inst Technol Hangzhou 311200 Peoples R China Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2522 Australia Natl Lab Radar & Surveillance Syst RaSS CNIT Pisa Italy Beijing Inst Technol Key Lab Elect & Informat Technol Satellite Nav Minist Educ Beijing 100081 Peoples R China Natl Lab Radar & Surveillance Syst CNIT I-56124 Pisa Italy

Sparse Bayesian learning (SBL) has found successful applications in interferometric inverse synthetic aperture radar (InISAR) imaging, especially in the presence of limited number of pulses or when using sparse apertures. SBL-based InISAR algorithms have been proven to be significantly superior to Fourier transform-based ones. However, the existing SBL-based algorithms are slow due to their high computational complexity. Moreover, there is also much room to improve in terms of imaging performance. In this article, leveraging the approximate message passing with unitary transformation (UAMP), we propose an InISAR imaging algorithm named UAMP joint sparse recovery (JSR), which is much faster and delivers notably higher imaging accuracy than the existing SBL-based algorithms. Specifically, we develop a type-2 joint sparse model for InISAR imaging and formulate it as a two-layer multiple measurement vectors joint sparse problem. Based on a factor graph representation, the message passing techniques are used to efficiently solve this problem, which leads to the UAMP-JSR algorithm. Results based on extensive simulations and experiments based on the real data collected by the Pisa Radar demonstrate the effectiveness and superiority of the proposed algorithm compared to existing algorithms.

关键词： Imaging Radar imaging approximation algorithms Three-dimensional displays Signal processing algorithms Antenna measurements Spaceborne radar Interferometric inverse synthetic aperture radar (InISAR) joint sparse recovery sparse Bayesian learning (SBL) unitary transformation (UAMP)

来源：评论

学校读者我要写书评

暂无评论

Online Pricing Incentive to Sample Fresh Information

引用

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2023年第1期10卷 514-526页

作者： Li, Hongbo Duan, Lingjie Singapore Univ Technol & Design Pillar Engn Syst & Design Singapore 487372 Singapore

Today mobile users such as drivers are invited by content providers (e.g., Tripadvisor) to sample fresh information of diverse paths to control the age of information (AoI). However, selfish drivers prefer to travel through the shortest path instead of the others with extra costs in time and gas. To motivate drivers to route and sample diverse paths, this paper is the first to propose online pricing for a provider to economically reward drivers for diverse routing and control the actual AoI dynamics over time and spatial path domains. This online pricing optimization problem should be solved without knowing drivers' costs and even arrivals, and is intractable due to the curse of dimensionality in both time and space. If there is only one non-shortest path, we leverage the Markov decision process (MDP) techniques to analyze the problem. Accordingly, we design a linear-time algorithm for returning optimal online pricing, where a higher pricing reward is needed for a larger AoI. If there are a number of non-shortest paths, we prove that pricing one path at a time is optimal, yet it is not optimal to choose the path with the largest current AoI. Then we propose a new backward-clustered computation method and develop an approximation algorithm to alternate different paths to price over time. Perhaps surprisingly, our analysis of approximation ratio suggests that our algorithm's performance approaches closer to optimum given more paths.

关键词： Pricing Vehicles Costs approximation algorithms Heuristic algorithms Routing Roads Age of information approximation error online multi-path pricing polynomial-time algorithms

来源：评论

学校读者我要写书评

暂无评论

Incremental Non-Gaussian Inference for SLAM Using Normalizing Flows

引用

IEEE TRANSACTIONS ON ROBOTICS 2023年第2期39卷 1458-1475页

作者： Huang, Qiangqiang Pu, Can Khosoussi, Kasra Rosen, David M. Fourie, Dehann How, Jonathan P. Leonard, John J. MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA MIT Dept Nucl Sci & Engn Cambridge MA 02139 USA CSIRO Robot & Autonomous Syst Grp DATA61 Brisbane Qld 4069 Australia Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA Northeastern Univ Dept Math Boston MA 02115 USA NavAbility Boston MA 02110 USA MIT Dept Aeronaut & Astronaut Engn Cambridge MA 02139 USA

This paper presents normalizing flows for incremental smoothing and mapping (NF-iSAM), a novel algorithm for inferring the full posterior distribution in SLAM problems with nonlinear measurement models and non-Gaussian factors. NF-iSAM exploits the expressive power of neural networks, and trains normalizing flows to model and sample the full posterior. By leveraging the Bayes tree, NF-iSAM enables efficient incremental updates similar to iSAM2, albeit in the more challenging non-Gaussian setting. We demonstrate the advantages of NF-iSAM over state-of-the-art point and distribution estimation algorithms using range-only SLAM problems with data association ambiguity. NF-iSAM presents superior accuracy in describing the posterior beliefs of continuous variables (e.g., position) and discrete variables (e.g., data association).

关键词： Simultaneous localization and mapping Inference algorithms approximation algorithms Task analysis Particle separators Belief propagation Random variables Bayes tree distribution estimation non-Gaussian normalizing flows SLAM

来源：评论

学校读者我要写书评

暂无评论

GRLF-LAD Control Based Active Power Filter Operation With QSG-SOGI Algorithm for Grid Voltage Harmonics Disturbance Rejection

引用

IEEE ACCESS 2023年 11卷 135753-135763页

作者： Aijaz, Masiha Hussain, Ikhlaq Lone, Shameem Ahmad Chankaya, Mukul Natl Inst Technol Srinagar Dept Elect Engn Srinagar 190006 Jammu & Kashmir India Vellore Inst Technol Sch Elect Engn Vellore Campus Vellore 632014 Tamil Nadu India

This article presents application of generalized robust logarithmic family (GRLF) framework derived least absolute difference (LAD) Algorithm implemented for active power filters (APF) for PQ enhancement. The presented GRLF-LAD algorithm successfully eliminates lower as well as higher order errors from the harmonically rich nonlinear load currents and thus results in accurate fundamental component extraction. Weak power grids are characterised by distorted grid voltages and riddled with inherent harmonics. Conventional techniques such as synchronous reference frame (SRF) algorithm are unable to filter out the harmonics from grid voltages and this results in oscillations in D-Q components. This leads to generation of a distorted reference current and thus unsatisfactory APF performance. In this article, the grid voltages are processed by modified second-order generalized integrator with quadrature signal generator (QSG-SOGI) based algorithm. The harmonic rejection capabilty of QSG-SOGI is far superior than other tested algorithms. QSG-SOGI shows remarkable improvement of approximately 99.35% than SRF and 96.02% than SOGI in terms of percentage improvement. The performance of presented APF is verified experimentally on a developed prototype and tested rigorously against load variations, grid voltage variations as well as grid distortions. The GRLF-LAD algorithm is found to be approximately 36.04% faster than APA and about 45.16% faster than LMS in terms of dynamic response and about 11.19% better than LMS in accurate current component extraction. The total harmonic distortion (THD) content of presented algorithm is found to be well within the IEEE-519 std.

关键词： Power harmonic filters Active filters Harmonic analysis Heuristic algorithms approximation algorithms Distortion Voltage control Power quality active power filter adaptive controls polluted grid conditions grid voltage harmonic reduction

来源：评论

学校读者我要写书评

暂无评论

Scheduling on a graph with release times

引用

JOURNAL OF SCHEDULING 2023年第6期26卷 571-580页

作者： Yu, Wei Golin, Mordecai Zhang, Guochuan East China Univ Sci & Technol Dept Math Shanghai 200237 Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Kowloon Clear Water Bay Hong Kong Peoples R China Zhejiang Univ Coll Comp Sci Hangzhou 310027 Peoples R China

We study a generalization of the well-known traveling salesman problem in a metric space, in which each city is associated with a release time. The salesman has to visit each city at or after its release time. There exists a naive 5/2-approximation algorithm where the salesman simply starts to route the network after all cities are released. Interestingly, this bound has never been improved for more than two decades. In this paper, we revisit the problem and achieve the following results. First, we devise an approximation algorithm with performance ratio less than 5/2 when the number of distinct release times is fixed. Then, we analyze a natural class of algorithms and show that no performance ratio better than 5/2 is possible unless the Metric TSP can be approximated with a ratio strictly less than 3/2, which is a well-known longstanding open question. Finally, we consider a special case where the graph has a heavy edge and present an approximation algorithm with performance ratio less than 5/2.

关键词： Vehicle scheduling problem Traveling salesman problem approximation algorithms Performance ratio

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：