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检索条件"主题词=approximation algorithms"

共 32005 条记录，以下是4971-4980 订阅

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Joint Design of Trajectory and Near-Field Beamforming for STAR-RIS-Enabled ISAC

Joint Design of Trajectory and Near-Field Beamforming for ST...

引用

International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Qiulei Huang Zhaohui Song Zehui Xiong Guanjun Xu Nan Zhao Dusit Niyato School of Information and Communication Engineering Dalian University of Technology Dalian China Space Information Research Institute Hangzhou Dianzi University Hangzhou China Singapore University of Technology and Design Singapore College of Computing and Data Science Nanyang Technological University Singapore

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) can be assembled in the air-ground integrated sensing and communication (ISAC) to further enhance the performance. However, the near-field effect should be further considered with higher carrier frequency and increasing number of STAR-RIS elements. In this paper, we propose a STAR-RIS enabled air-ground near-field ISAC scheme, where the unmanned aerial vehicle (UAV) is deployed as a mobile base station and the semi-passive architecture is adopted to alleviate the severe path loss. We maximize the weighted sum rate to guarantee both the communication and sensing by modifying the beamforming vectors, the reflection/transmission matrices and the hovering location of UAV to match the near-field effect. To address this challenge, we first divide it into three subproblems, which are recast into convex ones by the semidefinite relaxation and successive convex approximation. Finally, we develop an alternate algorithm to iteratively solve them. Simulation results are shown to demonstrate the superiority and validity of the proposed scheme.

关键词： Wireless communication Array signal processing Signal processing algorithms Reconfigurable intelligent surfaces Integrated sensing and communication Autonomous aerial vehicles approximation algorithms Vectors Air to ground communication Trajectory

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Resistance Eccentricity in Graphs: Distribution, Computation and Optimization

Resistance Eccentricity in Graphs: Distribution, Computation...

引用

International Conference on Data Engineering

作者： Zenan Lu Xiaotian Zhou Ahad N. Zehmakan Zhongzhi Zhang School of Computer Science Fudan University Shanghai China School of Computing Australian National University Canberra Australia

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

We study resistance eccentricity, a fundamental metric in network science for measuring the structural significance of a node. For a node in a graph, the resistance eccentricity is its maximum resistance distance to all other nodes. Fast computation of resistance eccentricity for a given subset of nodes is essential for a wide range of applications. However, a naive computation, requiring the pseudoinverse of the graph Laplacian, takes cubic time and is thus infeasible for huge networks with millions of nodes. In this paper, we devise a near-linear time algorithm to approximate the resistance eccentricity for one or multiple given nodes, accompanied by a theoretically guaranteed error bound. Furthermore, we investigate the problem of minimizing the resistance eccentricity for a given node by adding $k$ missing edges to the graph, for a budget $k$ . We show that while the objective function is monotone, it does not possess the submodularity property, ruling out the classical hill-climbing algorithm with theoretical guarantees. Instead, we propose two fast heuristic algorithms to approximately solve this problem. Then, we conduct extensive experiments on different networks with sizes up to several million nodes, demonstrating the superiority of our algorithms in terms of efficiency and effectiveness.

关键词： Resistance Measurement Laplace equations Heuristic algorithms Instruments Refining approximation algorithms

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Synthesis of Approximate Parametric Circuits for Variational Quantum algorithms

Synthesis of Approximate Parametric Circuits for Variational...

引用

Quantum Computing and Engineering (QCE), IEEE International Conference on

作者： Blake Burgstahler Ellis Wilson Scott Pakin Frank Mueller North Carolina State University Los Alamos National Laboratory

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

This work presents a novel approach to synthesize approximate circuits for the ansatze of variational quantum algorithms (VQA) and demonstrates its effectiveness in the context of solving integer linear programming (ILP) problems. Synthesis is generalized to produce parametric circuits in close approximation of the original circuit and to do so offline . This removes synthesis from the (online) critical path between repeated quantum circuit executions of VQA. We hypothesize that this approach will yield novel high fidelity results beyond those discovered by the baseline without synthesis. Simulation and real device experiments complement the baseline in finding correct results in many cases where the baseline fails to find any and do so with on average 32% fewer CNOTs in circuits.

关键词： Quantum algorithm Program processors Logic gates Integer linear programming approximation algorithms Quantum circuit

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Distributed Stochastic Optimisation with Uncertain Coupling Constraints

Distributed Stochastic Optimisation with Uncertain Coupling ...

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IEEE Conference on Decision and Control

作者： Alessandro Del Duca Fredy Ruiz Riccardo Scattolini Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano Milano Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Large-scale multi-agent systems are increasingly relevant in various aspects of society; their operation requires advances in multi-agent distributed optimisation algorithms that can handle uncertain environments. This paper presents a distributed algorithm suitable for solving convex constraint-coupled multi-agent problems with uncertainty directly affecting the coupling constraints. The algorithm exploits the problem structure to solve the large-scale uncertain problem efficiently, leveraging the scenario approach to approximate the coupling chance-constraint. We prove that the number of scenarios required to guarantee a given violation probability level is independent of the agent number, making the solution scalable. We apply the algorithm to a multi-microgrid aggregation problem to provide ancillary services to the Grid, a relevant decarbonisation and energy security topic.

关键词： Couplings Uncertainty approximation algorithms Probabilistic logic Low carbon economy Security Forecasting Distributed algorithms Optimization Multi-agent systems

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Heuristic vs. Analytical Energy Hub Optimization: Design, Implementation, and Trade-Offs

Heuristic vs. Analytical Energy Hub Optimization: Design, Im...

引用

IEEE International Conference on Smart Energy Grid Engineering (SEGE)

作者： Simon Grafenhorst Jakob Ohm Rafael Poppenborg Kevin Förderer Veit Hagenmeyer Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Karlsruhe Germany

ISBN: (数字)9798350377378

ISBN: (纸本)9798350377385

Various algorithms can be used to optimize the operation of energy hubs, which differ in complexity and optimization quality. The heuristic Evolutionary Algorithm (EA) is able to approximate solutions to complex and non-convex problems. In comparison, the Mixed-Integer Linear Programming (MILP) and the Mixed-Integer Quadratic Program (MIQP) are able to compute the optimal solution of an approximated model. The present paper focuses on the comparison of energy hub schedule optimization using an EA, a MILP, and a MIQP. Furthermore, the source code for the MILP and MIQP models is publicly available. In our comparison, the analytical solver can optimize the schedule of an exemplary energy hub within seconds, and the EA takes multiple minutes to compute. The schedule generated with the analytical models follows the target closely with a similar root-mean-square error as the schedule generated by the EA.

关键词： Schedules Analytical models Computational modeling Source coding Evolutionary computation approximation algorithms Mixed integer linear programming Complexity theory Optimization

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Joint Green and Deadline-Aware Path Planning for Rotary-Wing UAV-Assisted Internet-of-Things

Joint Green and Deadline-Aware Path Planning for Rotary-Wing...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Akram Khelili Halima Elbiaze Essaid Sabir Computer Science Department Université du Québec à Montréal (UQAM) Montreal Quebec Canada Department of Science and Technology TÈLUQ 5800 Denis st Montreal Quebec Canada

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

This paper proposes two unmanned aerial vehicles (UAV) trajectory planning solutions taking into consideration mission deadline, energy consumption, and communication constraints. The problem is mathematically formulated as a mult-iobjective optimization problem. The NP-hardness complexity is demonstrated then two heuristic solutions are proposed. Specifically, we first present a near-optimal UAV trajectory planning algorithm that reduces the number of stop/hovering points. Then, we propose an artificial bee colony-based algorithm with enhanced candidate selection. Extensive simulation results show that both our schemes outperform the well-known Successive Convex approximation (SCA) technique, under low-moderate traffic demand. They perform as well as SCA under high demand.

关键词： Energy consumption Trajectory planning Simulation Autonomous aerial vehicles approximation algorithms Complexity theory Optimization Land mobile radio

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PACE: A Piece-Wise Approximate and Configurable Floating - Point Divider for Energy - Efficient Computing

PACE: A Piece-Wise Approximate and Configurable Floating - P...

引用

Design, Automation and Test in Europe Conference and Exhibition

作者： Chenyi Wen Haonan Du Zhengrui Chen Li Zhang Qi Sun Cheng Zhuo Zhejiang University Hubei University Of Technology Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province China

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

Approximate computing is a promising alternative to improve energy efficiency for human perception related applications on the edge. This work proposes a piece-wise approximate floating-point divider, which is resource-efficient and run-time configurable. We provide a piece-wise approximation algorithm for 1/ y, utilizing powers of 2. This approach enables the implementation of a reciprocal-based floating-point divider that is independent of multipliers, which not only reduces hardware consumption but also results in shorter latency. Furthermore, a multi-level run-time configurable hardware structure is intro-duced, enhancing the adaptability to various application scenarios. When compared to the prior state-of-the-art approximate divider, the proposed divider strikes an advantageous balance between accuracy and resource efficiency. The application-level evaluation of the proposed dividers demonstrates manageable and minimal degradation of the output quality when compared to the exact divider.

关键词： Degradation Approximate computing Computer architecture approximation algorithms Hardware Energy efficiency Delays

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algorithms for Finding an Approximate Solution for Locating Obnoxious Facilities on Networks

Algorithms for Finding an Approximate Solution for Locating ...

引用

Dynamics of Systems, Mechanisms and Machines (Dynamics)

作者： Gennady Zabudsky Alexey Samatov Sobolev Institute of Mathematics of the Siberian Branch of the Russian Academy of Sciences Omsk Russia Dostoevsky Omsk State University Federal State Autonomous Educational Institution of Higher Education Omsk State Technical University Omsk Russia

ISBN: (数字)9798331509019

ISBN: (纸本)9798331509026

The problems of locating several obnoxious facilities on networks are studied. The facilities serve populated areas, but have a negative impact on the population. The negative impact decreases with increasing distance to the facilities. A mathematical model is given for an arbitrary number of the facilities. Approximate algorithms for solving of the problem for two facilities are developed. The original network is decomposed into two connected subnets. In each of the resulting subnet, the problem of locating one facility is solved using an exact algorithm. Calculations are performed on test examples for the shortest paths metric. For the case of network located on a plane, Euclidean metric and the shortest paths metric are used. Experiments to solve the problem on a road network of highways of France are conducted.

关键词： Measurement Heuristic algorithms Roads Euclidean distance approximation algorithms Mathematical models

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Dynamic Filter Length Reduction in NLMS for System Identification

Dynamic Filter Length Reduction in NLMS for System Identific...

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Measurement and Simulation (ATOMS), Advanced Topics on

作者： Elena-Valentina Dumitrașcu Robert-Alexandru Dobre Computers Department National University of Science and Technology Politehnica Bucharest Bucharest Romania Electronic Technology and Reliability National University of Science and Technology Politehnica Bucharest Bucharest Romania

ISBN: (数字)9798350358377

ISBN: (纸本)9798350358384

Adaptive filtering techniques are fundamental in system identification, enabling the estimation and modeling of unknown systems from observed input-output data. Among these methods, the Normalized Least Mean Squares (NLMS) algorithm holds paramount importance due to its versatility and widespread application in real-time adaptive signal processing. In system identification, NLMS algorithms serve as robust tools for approximating unknown systems by continuously adjusting the impulse response of adaptive filters based on incoming data. Conventional implementations of the NLMS algorithm assume a fixed filter length, creating challenges in scenarios where the length of the filter to be identified is unknown, thus hindering accurate system modeling, often leading to "overmodeling" and ineffective use of computational resources. This paper introduces an adaptation in the NLMS algorithm to dynamically modify the length of the adaptive filter, enhancing its computational resource efficiency. The proposed methodology addresses the challenge of accurately approximating unknown filters while decreasing the computational complexity. Simulation results demonstrate the efficacy of the proposed adaptive length modification technique, showcasing reduced computational overhead compared to traditional fixed-length NLMS methods, while still obtaining good misalignment values.

关键词： Adaptive systems Accuracy Filtering Heuristic algorithms Adaptive filters Signal processing algorithms Filtering algorithms approximation algorithms System identification Yield estimation

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Plan Balancing for Active Subsystems

Plan Balancing for Active Subsystems

引用

International Conference on Management of Large-Scale System Development (MLSD)

作者： Felix Ereshko Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

We consider decision making problems for player interaction model in two-level organization system. We state Center request consensus problem and system response in a common case of linear dependencies. We formulate balance conditions in the case of guaranteed consensus and possible good- will of the whole production. We present solution schemes to the mentioned problems and realization proofs.

关键词： Decision making Production Organizations approximation algorithms Large-scale systems

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