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Biennial Institute of Electrical and Electronics Engineers Conference on Electomagnetic Field Computation

作者： Christian Scheiblich Remus Banucu Veronika Reinauer Wolfgang M. Rucker Institute for Theory of Electrical Engineering University of Stuttgart

ISBN: (纸本)9781424470594

Today's low cost hardware developments allow for a parallelization of intensive computation processes over several selectable CPU cores by using Intel's OpenMP library. But if one applies this feature to a numerical simulation based on a boundary element method (BEM), there is still a huge bottle neck - the shared memory of such a system. So, if a low cost hardware should be effectively used for large BEM problems, a memory compression algorithm that is easily to be scheduled in parallel is of first choice. Within our new idea and development of the Hierarchical Block Wavelet Compression (HWC) which is based on IEEE's JPEG2000 standard for image compression, this bottle neck will be tackled in pure mathematically manners. Furthermore, its parallelization will be discussed and an optimal compression rate for a 3-D electrostatic BEM problem by a rather simple optimization algorithm will be presented.

关键词： optimization algorithms wavelet compression Parallel Lines compression ratio Data compression Hierarchical Bottles numerical simulation parallelization Image compression

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On the Methodology for the Evaluation of Unconstrained Multicast Routing algorithms

On the Methodology for the Evaluation of Unconstrained Multi...

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International Conference on Telecommunications (ICT)

作者： Maciej Stasiak Maciej Piechowiak Piotr Zwierzykowski Poznan University of Technology Poznan Poland Kazimierz Wielki University Bydgoszcz Poland

Having in mind various implementations of methods for generating network topology [1], [2], [3], there is also a need for a wider mechanism determining receiving nodes in a network by geographical positioning, or one that would be related to link and node parameters. This will allow us to answer the question whether the way receiving nodes are distributed has any influence on the quality of multicast trees constructed by algorithms. The paper proposes methods that arrange group members in packet-switched networks. In the research we discuss the influence of the group arrangement method on the total cost of tree and the average cost of path in a tree for unconstrained routing algorithms for multicast connections. The methods for the receiving nodes distribution in the network have not been hitherto addressed and analyzed in literature.

关键词： Multicast Routing algorithms Network topology optimization algorithms

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Ultra-thin Reconfigurable Electromagnetic Metasurface Absorbers

Ultra-thin Reconfigurable Electromagnetic Metasurface Absorb...

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European Conference on Antennas and Propagation

作者： Idellyse Martinez Anastasios H. Panaretos Douglas H. Werner Giacomo Oliveri Andrea Massa Department of Electrical Engineering The Pennsylvania State University University Park PA 16802 USA ELEDIA Research Center@DISI University of Trento Trento Italy

ISBN: (纸本)9781467321877

An ultra-thin reconfigurable absorber concept based on metasurfaces is presented. First, an artificial magnetic conducting (AMC) metasurface absorber is examined that incorporates lumped resistors along with variable lumped capacitors, which allow its frequency response to be tuned. The parasitic effects introduced by the lumped capacitors are compensated by adding resistors whose values are determined using an optimization algorithm known as the covariance matrix adaptation evolutionary strategy (CMA-ES). Second, the feasibility of achieving broadband absorption using frequency selective surfaces (FSSs) comprised of square loops is examined. Such a structure offers greater tunability, and thus wideband absorption can be achieved. First, an absorber that utilizes an FSS comprised by two square loops along with lumped resistors is studied and its wideband absorption properties are demonstrated. Second, an absorber that incorporates a resistive frequency selective surface comprised by four square loops and a center patch is presented.

关键词： frequency selective surfaces square loop optimization algorithms parasitic effect Resistor Device Component configurability broadband variance covariance matrix frequency response absorbers

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A parallel processor for distributed genetic algorithm with redundant binary number

A parallel processor for distributed genetic algorithm with ...

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International Conference on New Trends in Information and Service Science, NISS

作者： Tomohiro Kamimura Akinori Kanasugi Department of Electronics Tokyo Denki University Tokyo Japan

ISBN: (纸本)9781467308762

Genetic algorithm (GA) is one of optimization algorithm based on an idea for evolution of life. GA can be applied various combination optimization problem. This paper proposes a parallel processor for distributed genetic algorithm (DGA) with redundant binary number. Since a redundant binary number has redundancy, solution expression becomes variegated. For this reason, it is expected the algorithm easily find the optimized solution, and the error rates decrease. Since DGA is a parallel algorithm, the performance can be improved by using a specified parallel processor. The effectiveness of the proposed processor was confirmed by some simulations and experiments using FPGA circuit board.

关键词： Component Parallel processor Distributed GA Redundant binary number concurrent processor Binary digits Error analysis Genetic Algorithm (GA) Redundant optimization algorithms

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Branch-and-cut algorithms for colorful components problems

arXiv

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arXiv 2024年

作者： Archetti, Claudia Cerulli, Martina Sorgente, Carmine Department of Information Systems Decision Sciences and Statistics ESSEC Business School Cergy-Pontoise France Department of Computer Science University of Salerno Fisciano Italy Department of Mathematics University of Salerno Fisciano Italy

We tackle three optimization problems in which a colored graph, where each node is assigned a color, must be partitioned into colorful connected components. A component is defined as colorful if each color appears at most once. The problems differ in the objective function, which determines which partition is the best one. These problems have applications in community detection, cybersecurity, and bioinformatics. We present integer non-linear formulations, which are then linearized using standard techniques. To solve these formulations, we develop exact branch-and-cut algorithms, embedding various improving techniques, such as valid inequalities, bounds limiting the number of variables, and warm-start and preprocessing techniques. Extensive computational tests on benchmark instances demonstrate the effectiveness of the proposed procedures. The branch-and-cut algorithms can solve reasonably sized instances efficiently. To the best of our knowledge, we are the first to propose an exact algorithm for solving these problems. Copyright © 2024, The Authors. All rights reserved.

关键词： optimization algorithms

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Exact Penalization at D-Stationary Points of Cardinality- or Rank-Constrained Problem

arXiv

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arXiv 2022年

作者： Yagishita, Shotaro Gotoh, Jun-Ya The Institute of Statistical Mathematics Japan Department of Data Science for Business Innovation Chuo University Japan

This paper studies the properties of d-stationary points of the trimmed lasso (Luo et al., 2013, Huang et al., 2015, and Gotoh et al., 2018) and the composite optimization problem with the truncated nuclear norm (Gao and Sun, 2010, and Zhang et al., 2012), which are known as tight relaxations of nonconvex optimization problems that have either cardinality or rank constraints, respectively. First, we extend the trimmed lasso for broader applications and for conducting a unified analysis of the property of the generalized trimmed lasso. Next, the equivalence between local optimality and d-stationarity of the generalized trimmed lasso is shown under a suitable assumption. More generally, the equivalence is shown for problems that minimize a function defined by the pointwise minimum of finitely many convex functions. Then, we present new results of the exact penalty at d-stationary points of the generalized trimmed lasso and the problem with the truncated nuclear norm penalty under mild assumptions. Our exact penalty results are not only new, but also intuitive, so that we can see what properties of the problems play a role for establishing the exact penalization. Lastly, matters relating to algorithms are also discussed. Copyright © 2022, The Authors. All rights reserved.

关键词： optimization algorithms

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Optimal confidence interval for the difference of proportions

arXiv

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arXiv 2023年

作者： Peer, Almog Azriel, David Technion - Israel Institute of Technology Israel

Estimating the probability of the binomial distribution is a basic problem, which appears in almost all introductory statistics courses and is performed frequently in various studies. In some cases, the parameter of interest is a difference between two probabilities, and the current work studies the construction of confidence intervals for this parameter when the sample size is small. Our goal is to find the shortest confidence intervals under the constraint of coverage probability being at least as large as a predetermined level. For the two-sample case, there is no known algorithm that achieves this goal, but different heuristics procedures have been suggested, and the present work aims at finding optimal confidence intervals. In the one-sample case, there is a known algorithm that finds optimal confidence intervals presented by Blyth and Still (1983). It is based on solving small and local optimization problems and then using an inversion step to find the global optimum solution. We show that this approach fails in the two-sample case and therefore, in order to find optimal confidence intervals, one needs to solve a global optimization problem, rather than small and local ones, which is computationally much harder. We present and discuss the suitable global optimization problem. Using the Gurobi package we find near-optimal solutions when the sample sizes are smaller than 15, and we compare these solutions to some existing methods, both approximate and exact. We find that the improvement in terms of lengths with respect to the best competitor varies between 1.5% and 5% for different parameters of the problem. Therefore, we recommend the use of the new confidence intervals when both sample sizes are smaller than 15. Tables of the confidence intervals are given in the Excel file in this link. © 2023, CC BY.

关键词： optimization algorithms

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OPTIMAL algorithms AND CRB FOR RECIPROCITY CALIBRATION IN MASSIVE MIMO

OPTIMAL ALGORITHMS AND CRB FOR RECIPROCITY CALIBRATION IN MA...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Kalyana Gopala Dirk Slock EURECOM Sophia-Antipolis France

ISBN: (纸本)9781538646595

Gains from Massive MIMO are crucially dependent on the availability of channel state information at the transmitter which is far too costly if it has to estimated directly. Hence, for a time division duplexing system, this is derived from the uplink channel estimates using the concept of channel reciprocity. However, while the propagation channel is reciprocal, the overall digital channel in the downlink also involves the radio frequency chain which is non-reciprocal. This calls for calibration of the uplink channel with reciprocity calibration parameters to derive the downlink channel estimates. Initial approaches towards estimation of the reciprocity calibration parameters [1, 2] were all based on least squares. An ML estimator and a CRB for the estimators was introduced in [3]. This paper presents a more elegant and accurate CRB expression for a general reciprocity calibration framework. An optimal algorithm based on Variational Bayes is presented and it is compared with existing algorithms.

关键词： Masive MIMO Reciprocity Calibration CRB complementary return to bias reciprocity calibration Channel state information optimization algorithms

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Motion Part Regularization: Improving Action Recognition via Trajectory Group Selection

Motion Part Regularization: Improving Action Recognition via...

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Bingbing Ni Pierre Moulin Xiaokang Yang Shuicheng Yan ADSC Singapore Singapore

ISBN: (纸本)9781467369657

Dense local trajectories have been successfully used in action recognition. However, for most actions only a few local motion features (e.g., critical movement of hand, arm, leg etc.) are responsible for the action label. Therefore, highlighting the local features which are associated with important motion parts will lead to a more discriminative action representation. Inspired by recent advances in sentence regularization for text classification, we introduce a Motion Part Regularization framework to mine for discriminative groups of dense trajectories which form important motion parts. First, motion part candidates are generated by spatio-temporal grouping of densely extracted trajectories. Second, an objective function which encourages sparse selection for these trajectory groups is formulated together with an action class discriminative term. Then, we propose an alternative optimization algorithm to efficiently solve this objective function by introducing a set of auxiliary variables which correspond to the discriminativeness weights of each motion part (trajectory group). These learned motion part weights are further utilized to form a discriminativeness weighted Fisher vector representation for each action sample for final classification. The proposed motion part regularization framework achieves the state-of-the-art performances on several action recognition benchmarks.

关键词： trajectory Objective function Group selection Action Text categorization moving parts Recognition (Psychology) optimization algorithms

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Breaking the Speed and Scalability Barriers for Graph Exploration on Distributed-memory Machines 12

Breaking the Speed and Scalability Barriers for Graph Explor...

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ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis

作者： Fabio Checconi Fabrizio Petrini Jeremiah Willcock Andrew Lumsdaine Anamitra Roy Choudhury Yogish Sabharwal IBM TJ Watson Yorktown Heights NY 10598 CREST Indiana University Bloomington IN 47405 IBM India Research New Delhi DL 110070 India

ISBN: (纸本)9781467308052

In this paper, we describe the challenges involved in designing a family of highly-efficient Breadth-First Search (BFS) algorithms and in optimizing these algorithms on the latest two generations of Blue Gene machines, Blue Gene/P and Blue Gene/Q. With our recent winning Graph 500 submissions in November 2010, June 2011, and November 2011, we have achieved unprecedented scalability results in both space and size. On Blue Gene/P, we have been able to parallelize a scale 38 problem with 2~(38) vertices and 2~(42) edges on 131,072 processing cores. Using only four racks of an experimental configuration of Blue Gene/Q, we have achieved a processing rate of 254 billion edges per second on 65,536 processing cores. This paper describes the algorithmic design and the main classes of optimizations that we have used to achieve these results.

关键词： Distributed-memory Machines BFS Blue Gene machines BUNDESAMT FUER STRAHLENSCHUTZ speed Scalability color blue distributed memory machine machinery Line graph optimization algorithms

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