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SPIE Conference on Acquisition, Pointing, and Tracking

作者： Gordon, NJ Salmond, DJ Everett, NO Defence Evaluation and Research Agency (United Kingdom)

ISBN: (纸本)0819428140

A Bayesian technique is applied to the target acquisition problem at handover from the fire control to the missile seeker. This is a multiple hypothesis scheme which includes an explicit model of the possible misalignment or bias between the fire control and seeker coordinate frames. This method is compared with a linear least cost assignment technique which may be implemented via the munkres fast search algorithm.

关键词： target acquisition Bayesian methods multiple hypothesis methods munkres algorithm

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Kuhn-munkres algorithm-Based Matching Method and Automatic Device for Tiny Magnetic Steel Pair

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MICROMACHINES 2021年第3期12卷 316-316页

作者： Xu, Zheng Yuan, Guo-zhao Wang, Xiao-dong Quan, Xian-shuai Ren, Tong-qun Liu, Jun-shan Dalian Univ Technol Key Lab Micro Nano Technol & Syst Liaoning Prov Dalian 116024 Peoples R China

The tiny magnetic steel pair (TMSP), composed by two tiny magnetic steel blocks (TMSBs), is critical for some precision instruments. Incorrect matching of TMSP may result in insufficient instrument performance. Herein, the matching method of TMSP based on the Kuhn-munkres algorithm is proposed. Further, an automatic TMSP matching device is developed. Especially, an ingenious clamp for multiple constraints of TMSB is presented and a visual/magnetism/force hybrid control strategy is realized for the safe and efficient manipulation of TMSBs in a magnetic environment. Moreover, with the TMSBs of a pendulum accelerometer, the matching experiments are conducted to validate the comprehensive performance. The result of the numerical experiment shows that the Kuhn-munkres algorithm-based method is stable and efficient. The results of measurement and TMSP matching experiments show that the device has good repeatability (<1 mT) and practicability. The proposed matching method has great application prospect in various matching and microassembly of TMSPs.

关键词： tiny magnetic steel pair Kuhn– munkres algorithm matching method microassembly

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Whale Optimization-Based Access Control Scheme in D2D Communication Underlaying Cellular Networks

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IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT 2024年第3期21卷 3416-3427页

作者： Jadav, Nilesh Kumar Tanwar, Sudeep Nirma Univ Inst Technol Dept Comp Sci & Engn Ahmadabad 382481 India

Integration of device-to-device (D2D) communication has gained significant attention within cellular networks as a means to enhance their capacity, coverage, and performance. Despite these advantages, D2D communication encounters various challenges, such as high interference, resource allocation, energy efficiency, and security. In this paper, we investigate the problem associated with resource allocation in D2D communication underlying cellular networks. The existing resource allocation schemes (e.g., game theory and graph theory) do not offer an access control mechanism, due to which the existing schemes are computationally intensive and do not converge to offer a global optimum solution. Toward this goal, we proposed a whale optimization algorithm(WOA)-based access control scheme to enhance the performance of the resource allocation scheme in D2D communication. In WOA, we created a signal-to-interference-plus-noise ratio (SINR)-based objective function that iteratively discovers the best D2D users, allowing them to participate in the resource allocation process. Moreover, for resource allocation, we adopted the munkres algorithm, which allows only optimized D2D users (from WOA) to reuse the resources of cellular users (CUs). In the proposed work, WOA acts as an access control scheme that optimally finds the best D2D users and only allows them to reuse cellular resources in the munkres resource assignment problem. Simulation results show that the proposed scheme significantly improves the system's throughput compared to other existing algorithms. Moreover, other evaluation parameters, such as convergence rate, fairness, WOA update positions, and execution time, show the outperformance of the proposed scheme.

关键词： Whale optimization algorithm evolutionary algorithm D2D communication optimization meta heuristic algorithm munkres algorithm Whale optimization algorithm evolutionary algorithm D2D communication optimization meta heuristic algorithm munkres algorithm

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Statistical CSIT Aided User Scheduling for Broadcast MU-MISO System

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2017年第7期66卷 6102-6114页

作者： Cao, Qi Sun, Yanjing Ni, Qiang Li, Song Tan, Zefu China Univ Min Technol Sch Informat & Control Engn Xuzhou 221116 Peoples R China Univ Lancaster Sch Comp & Commun InfoLab21 Lancaster LA1 4YW England

Recent studies show that the statistical channel state information (SCSI) helps to largely increase the capacity of communication systems when the instantaneous perfect CSI is unavailable. In this paper, we consider multiuser multiple-inputsingle-output broadcast channels where the transmitter has the knowledge of SCSI. The major issue of concern in our paper is to improve the average group-rate of the whole system by scheduling users over different time slots. With SCSI at the transmitter side, we are able to precode signals and, hence, compute the theoretical achievable group-rate of arbitrary user groups. Based on the group-rates, we propose tier-2munkres user scheduling algorithm (T2-MUSA) that leads to higher average group-rate than existing algorithms with generally better fairness. The optimality of the proposed algorithm in energy-fair user scheduling space is proved and we derive a lower bound of a special case to verify the validity of our simulations. In addition, many conventional user scheduling algorithms maintain queue stability by solving a weighted sum-rate (WSR) problem, using queue lengths to represent weight coefficients. Inspired by T2-MUSA, we propose a QoS-based MUSA (QB-MUSA) aimed at stabilizing queue lengths and maximizing throughput. In results, we show that QB-MUSA exhibits higher throughput than the conventional WSR-based algorithm.

关键词： Multiple-input single-output (MISO) multiuser (MU) scheduling munkres algorithm statistical channel state information (SCSI)

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Fast computation of Bipartite graph matching

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PATTERN RECOGNITION LETTERS 2014年 45卷 244-250页

作者： Serratosa, Francesc Univ Rovira & Virgili Tarragona Catalonia Spain

We present a new algorithm to compute the Graph Edit Distance in a sub-optimal way. We demonstrate that the distance value is exactly the same than the one obtained by the algorithm called Bipartite but with a reduced run time. The only restriction we impose is that the edit costs have to be defined such that the Graph Edit Distance can be really defined as a distance function, that is, the cost of insertion plus deletion of nodes (or arcs) have to be lower or equal than the cost of substitution of nodes (or arcs). Empirical validation shows that higher is the order of the graphs, higher is the obtained Speed up. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Graph Edit Distance Bipartite graph matching munkres algorithm

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Memetic algorithms applied to the optimization of workflow compositions

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SWARM AND EVOLUTIONARY COMPUTATION 2013年 10卷 31-40页

作者： Ludwig, Simone A. N Dakota State Univ Dept Comp Sci Fargo ND 58105 USA

The selection of services of a workflow based on Quality of Service (QoS) attributes is an important issue in service-oriented systems. QoS attributes allow for a better selection process based on nonfunctional quality criteria such as reliability, availability, and response time. Past research has mostly addressed this problem with optimal methods such as linear programming approaches. Given the nature of service-oriented systems where large numbers of services are available with different QoS values, optimal methods are not suitable and therefore, approximate techniques are necessary. In this paper, we investigate Genetic algorithms and particle swarm optimization for the service selection process. In particular, both methods are combined with an optimal assignment algorithm (munkres algorithm) in order to achieve higher solution qualities (success ratios) and to form a so called memetic algorithm. Experiments are conducted to investigate the suitability of the approaches and to compare the memetic algorithms with their non-memetic counterparts. The results reveal that the memetic algorithms are very suitable for the application to the workflow selection problem. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Genetic algorithms Particle swarm optimization munkres algorithm Quality of service Memetic algorithms

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Robust Control with Optimization of Robustness Index

Robust Control with Optimization of Robustness Index

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Giernacki, Wojciech Poznan Univ Tech Inst Control & Informat Engn Poznan Poland

ISBN: (纸本)9781467317146

The paper considers a problem of robust control system synthesis based on the modified algorithm of Coefficient Diagram Method (CDM) with robustness index optimization. The proposed solution is expected to enable improvement of system robustness against parametric uncertainty. As a measure of assessment an aim function (robustness index) defined for the system with an additional filter block is introduced. Parameters of this block are calculated with the use of Hungarian (munkres) algorithm. The controller synthesis is presented in a theory and on an example. A description of the proposed, modified CDM algorithm and optimization procedure are given, as well as the specification of the coefficient diagram (CD) - a tool for assessment of system stability, robustness and dynamics. The design problem is formulated for the system with stable nonminimum phase plant. Paper presents results of optimization and simulation tests performed in MATLAB 7.0 environment, which confirmed the efficiency of the proposed solution.

关键词： robust control coefficient diagram method pole placement robustness index optimization munkres algorithm

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Robust Control with Optimization of Robustness Index

Robust Control with Optimization of Robustness Index

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Wojciech Giernacki Institute of Control and Information Engineering Poznan University of Technology

ISBN: (纸本)9781467317139

关键词： Robust control Coefficient diagram method Pole placement Robustness index optimization munkres algorithm Robust control simulation test design problems Optimization Procedure Robustness Certified emission reductions CDM control system synthesis Specifications

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A study of clustering applied to multiple target tracking algorithm 04

A study of clustering applied to multiple target tracking al...

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Proceedings of the 5th international conference on Computer systems and technologies

作者： Pavlina Konstantinova Milen Nikolov Tzvetan Semerdjiev Institute for Parallel Processing BAS Sofia

ISBN: (纸本)9789549641387

In this paper the effectiveness of two Data Association algorithms for Multiple Target Tracking (MTT) based on Global Nearest Neighbor approach are compared. As the time for assignment problem solution increases nonlinearly depending on the problem size, it is useful to divide the whole scenario on small groups of targets called clusters. For each cluster the assignment problem is solved by using-munkres algorithm. Results reveal that the computational time especially for large scenarios decreases significantly when clustering is used.

关键词： data association multiple target tracking (MTT) global nearest neighbor (GNN) clustering munkres algorithm assignment problem

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A study of a target tracking algorithm using global nearest neighbor approach 03

A study of a target tracking algorithm using global nearest ...

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Proceedings of the 4th international conference conference on Computer systems and technologies: e-Learning

作者： Pavlina Konstantinova Alexander Udvarev Tzvetan Semerdjiev Central Laboratory for Parallel Processing BAS Sofia Central Laboratory for Parallel Processing BAS

ISBN: (纸本)9789549641332

This paper compares two algorithms for Multiple Target Tracking (MTT), using Global Nearest Neighbor (GNN) and Suboptimal Nearest Neighbor (SNN) approach respectively. For both algorithms the observations are divided in clusters to reduce computational efforts. For each cluster the assignment problem is solved by using munkres algorithm or according SNN rules. Results reveal that in some cases the GNN approach gives batter solution *** approach. The computational time, needed for assignment problem solution using munkres algorithm is studied and results prove that it is suitable for real time implementations.

关键词： munkres algorithm

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