Results 11 to 20 of about 453 (143)
Journal of MathematicsData completion techniques offer numerous advantages in various fields. However, completing large datasets that must satisfy specific criteria can be challenging, necessitating the use of approximative completion methods.
Hajar A. Alshaikh +2 more
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Improving the linear relaxation of maximum k-cut with semidefinite-based constraints
EURO Journal on Computational Optimization, 2019 We consider the maximum k-cut problem that involves partitioning the vertex set of a graph into k subsets such that the sum of the weights of the edges joining vertices in different subsets is maximized.
VilmarJefté Rodrigues de Sousa +2 more
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On the Embed and Project Algorithm for the Graph Bandwidth Problem
Mathematics, 2021 The graph bandwidth problem, where one looks for a labeling of graph vertices that gives the minimum difference between the labels over all edges, is a classical NP-hard problem that has drawn a lot of attention in recent decades. In this paper, we focus
Janez Povh
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Semidefinite Programming Algorithms for 3-D AOA-Based Hybrid Localization
IEEE Open Journal of Signal Processing, 2023 By taking different kinds of measurements at the same time, it may be possible to improve the accuracy of target localization or reduce the number of sensors needed.
Yanbin Zou
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Array pattern synthesis using semidefinite programming and a bisection method
ETRI Journal, 2019 In this paper, we propose an array pattern synthesis scheme using semidefinite programming (SDP) under array excitation power constraints. When an array pattern synthesis problem is formulated as an SDP problem, it is known that an additional rank‐one ...
Jong‐Ho Lee +3 more
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Faster quantum and classical SDP approximations for quadratic binary optimization [PDF]
Quantum, 2022 We give a quantum speedup for solving the canonical semidefinite programming relaxation for binary quadratic optimization. This class of relaxations for combinatorial optimization has so far eluded quantum speedups. Our methods combine ideas from quantum
Fernando G.S L. Brandão +2 more
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Alternative SDP and SOCP approximations for polynomial optimization
EURO Journal on Computational Optimization, 2019 In theory, hierarchies of semidefinite programming (SDP) relaxations based on sum of squares (SOS) polynomials have been shown to provide arbitrarily close approximations for a general polynomial optimization problem (POP).
Xiaolong Kuang +3 more
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Discrete-Time Indefinite Stochastic LQ Control via SDP and LMI Methods
Journal of Applied Mathematics, 2012 This paper studies a discrete-time stochastic LQ problem over an infinite time horizon with state-and control-dependent noises, whereas the weighting matrices in the cost function are allowed to be indefinite.
Shaowei Zhou, Weihai Zhang
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Mokslas: Lietuvos Ateitis, 2015 Semidefinite Programming (SDP) is a fairly recent way of solving optimization problems which are becoming more and more important in our fast moving world. It is a minimization of linear function over the intersection of the cone of positive semidefinite
Rasa Giniūnaitė
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Multipath Exploitation with Time Reversal Waveform Covariance Matrix for SNR Maximization
Remote Sensing, 2020 Radar target detection has a wide range of applications in the military and civilian remote sensing fields; in particular, the target detection in multipath environments has attracted many scholars’ attention in recent years.
Chao Xiong, Chongyi Fan, Xiaotao Huang
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