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检索条件"主题词=Concave Programming"

共 311 条记录，以下是221-230 订阅

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Towards a dominant-polytope complexity reduction in Explicit MPC

Towards a dominant-polytope complexity reduction in Explicit...

引用

International Conference on Process Control (PC)

作者： Stevek, Juraj Kvasnica, Michal Fikar, Miroslav Slovak Univ Technol Bratislava Fac Chem & Food Technol Inst Informat Engn Automat & Math Bratislava 81237 Slovakia

ISBN: (纸本)9781479909261;9781479909278

In this paper a complexity reduction method of explicit MPC based on a dominant polytope is proposed. When a partitioning of explicit MPC consists of many small regions and a single big region it is reasonable to expect more frequent call of the control law associated with the big region than another ones during the control performance. Such an organization of the regions favors the online evaluation of explicit MPC. In the paper a problem to find a dominant polytope over the regions that share the same affine control law is studied. The problem of finding maximum volume polytope inscribed in nonconvex area is known as potato peeling problem in the literature. In this paper we focus to find a suboptimal solution by means of stochastic search.

关键词： computational complexity computational geometry concave programming piecewise constant techniques predictive control search problems stochastic processes suboptimal control

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Nonlinear Non-convex Optimization of Hydraulic Networks

Nonlinear Non-convex Optimization of Hydraulic Networks

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IEEE International Conference on Control Applications (CCA)

作者： Tahavori, Maryamsadat Kallesoe, Carsten Leth, John Wisniewski, Rafael Aalborg Univ Dept Elect Syst Fredrik Bajers Vej 7 DK-9220 Aalborg Denmark Grundfos Management AS Bjerringbro Denmark

ISBN: (纸本)9781479915590

Pressure management in water supply systems is an effective way to reduce the leakage in a system. In this paper, the pressure management and the reduction of power consumption of a water supply system is formulated as an optimization problem. The problem is to minimize the power consumption in pumps and also to regulate the pressure at the end-user valves to a desired value. The optimization problem which is solved is a nonlinear and non-convex optimization. The barrier method is used to solve this problem. The modeling framework and the optimization technique which are used are general. They can be used for a general hydraulic networks to optimize the leakage and energy consumption and to satisfy the demands at the end-users. The results in this paper show that the power consumption of the pumps is reduced.

关键词： concave programming hydraulic systems nonlinear programming pressure control pumps water supply

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Decentralized Multi-Cell Beamforming with Base Station Cooperation

Decentralized Multi-Cell Beamforming with Base Station Coope...

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10th IEEE Consumer Communications and Networking Conference (CCNC)

作者： Bose, Sayak Deshmukh, Siddharth Natarajan, Balasubramaniam Kansas State Univ Dept Elect & Comp Engn Manhattan KS 66506 USA

ISBN: (纸本)9781467331333;9781467347358

This paper presents a design strategy for base station (BS) coordinated multi cell joint beamforming. Our objective is to maximize the average cell throughput while maintaining quality of service (QoS) for individual users. The QoS in our analysis relates to minimum signal to interference plus noise ratio (SINR) achieved by every user. Since, throughput maximization is a non convex problem, an optimal solution can not be obtained using polynomial order algorithms. However, it can be observed that existence of inter cell interference (ICI) terms are the cause of non convexity. With this knowledge, we propose two decentralized approaches based on primal and dual decomposition of the throughput maximization problem. As ICI terms are the shared variables between the base stations (BSs), these terms are exchanged between the neighboring BSs and kept fixed during an iteration. This fixes the non convex (ICI) terms, resulting in convex subproblems. We demonstrate the quality of our sub optimal decentralized solution by simulations and comparing it with optimal exhaustive search algorithms (Genie-aided algorithm). A comparison analysis is also presented for both primal and dual solutions.

关键词： array signal processing concave programming polynomials quality of service search problems

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Distributed Algorithm for SDP State Estimation

Distributed Algorithm for SDP State Estimation

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Conference of the IEEE PES on Innovative Smart Grid Technologies (ISGT)

作者： Weng, Yang Li, Qiao Negi, Rohit Ilic, Marija Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

ISBN: (纸本)9781467348966;9781467348942

Smart Grid State Estimation (SE) aims at providing robust and accurate system state estimate for subsequent control operations to accommodate the disturbance of highly intermittent components. Conventional SE for AC Power Grid formulates the estimation process as a non-convex optimization problem, which may reach a local optimal and stop. To compensate the drawback, Semidefinite programming (SDP) was recently applied to convexify the non-convex problem with rank one relaxation technique, which shows perspectives with approximately globally optimal estimate. However, as the SDP approach is essentially a centralized algorithm, it is computationally expensive and non-robust to partial network failure, bad data. etc. To ameliorate the current SDP SE approach, this paper presents a distributed algorithm by employing Lagrangian method and graph theory results and particularly by dividing power networks in accordance with network 'cliques'. Correspondingly, significant improvements are illustrated in simulations on IEEE test beds.

关键词： concave programming graph theory power system control power system state estimation robust control smart power grids

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Optimal SNR-based Coverage in Poisson Cellular Networks with Power Density Constraints

Optimal SNR-based Coverage in Poisson Cellular Networks with...

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Australian Communications Theory Workshop (AusCTW)

作者： Samarasinghe, Tharaka Inaltekin, Hazer Evans, Jamie S. Monash Univ Dept Elect & Comp Syst Engn Clayton Vic 3800 Australia

ISBN: (纸本)9781467346757;9781467346733

This paper studies the coverage maximization for wireless networks in which base station (BS) locations are drawn from a homogenous spatial Poisson point process, and user locations are arbitrary. A user is covered for communication if its received signal-to-noise-ratio (SNR) is above a given threshold value, and the objective is to maximize the coverage probability under per unit area power density constraints. The resulting optimization problem is solved analytically by making use of the underlying concavity in the objective function when transmissions are impaired only by a power-law bounded path loss. Our results show that the optimal transmit power per BS is independent of the power density constraint, and the solution to the optimization problem represents the Pareto optimal boundary between the power density constraint and the coverage probability. Then, these results are extended to a system in which transmissions are impaired by both path loss and fading. The resulting optimization problem with fading turns out to be a non-convex optimization problem. In this case, we provide tight upper bounds on the optimal coverage probability. The paper also discusses the importance of using bounded path loss models for coverage maximization problems in wireless networks, and shows that an unbounded model will lead to trivial solutions.

关键词： Pareto optimisation cellular radio concave programming probability stochastic processes

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A Sub-optimal Threshold-Based Power Allocation Scheme for Joint Transmission in HetNet

A Sub-optimal Threshold-Based Power Allocation Scheme for Jo...

引用

IEEE 78th Vehicular Technology Conference (VTC Fall)

作者： Xu, Yujie Zhou, Wen'an Liang, Te Ren, Xiaotao Beijing Univ Posts & Telecommun ICN&SEC Ctr Beijing Peoples R China HUAWEI Technol Co Ltd Res Dept Wireless Networks Beijing Peoples R China

ISBN: (纸本)9781467361873

We study the power allocation of Marco eNodeB (MeNB) for joint transmission in Range Expanding region of HetNet. We formulate the optimization problem of maximizing HetNet throughput. The original problem turns out to be a non-convex problem. To achieve high system throughput and reduce the complexity, we put forward a sub-optimal power allocation scheme, i.e., Threshold-Based Power Allocation (TBPA) scheme. In TBPA scheme, we analyze the optimal subcarrier assignment and then set a basic power threshold for MeNB. Based on the threshold, subcarriers are selected to allocate power. We mathematically prove the original non-convex problem is turned into a quasi-convex problem. We evaluate TBPA scheme and other interference coordination schemes under different parameters. The simulation results show that compared to the conventional interference coordination schemes, TBPA scheme can improve the system throughput by a large margin with limited complexity.

关键词： Internet computational complexity concave programming convex programming mobile computing radiofrequency interference

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Capacity of Compound MIMO Gaussian Channels with Additive Uncertainty

Capacity of Compound MIMO Gaussian Channels with Additive Un...

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IEEE International Symposium on Information Theory (ISIT)

作者： Sun, Yin Koksal, C. Emre Shroff, Ness B. Ohio State Univ Dept ECE Columbus OH 43210 USA

ISBN: (纸本)9781479904464

This paper considers reliable communications over a multiple-input multiple-output (MIMO) Gaussian channel, where the channel matrix is within a bounded channel uncertainty region around a nominal channel matrix, i.e., an instance of the compound MIMO Gaussian channel. We study the optimal transmit covariance design to achieve the capacity of compound MIMO Gaussian channels, where the channel uncertainty region is characterized by the spectral norm. This design problem is a challenging non-convex optimization problem. However, in this paper, we reveal that this design problem has a hidden convexity property, and hence it can be simplified as a convex optimization problem. Towards this goal, we first prove that the optimal transmit design is to diagonalize the nominal channel, and then show that the duality gap between the capacity of the compound MIMO Gaussian channel and the minimal channel capacity is zero, which proves the conjecture of Loyka and Charalambous (IEEE Trans. Inf. Theory, vol. 58, no. 4, pp. 2048-2063, 2012). The key tools for showing these results are a novel matrix determinant inequality and some unitarily invariant properties.

关键词： Gaussian channels MIMO communication concave programming convex programming determinants matrix algebra telecommunication network reliability

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Optimal Location and Sizing of Distributed Storage Systems in Active Distribution Networks

Optimal Location and Sizing of Distributed Storage Systems i...

引用

IEEE Grenoble PowerTech (POWERTECH) Conference

作者： Nick, M. Hohmann, M. Cherkaoui, R. Paolone, M. Ecole Polytech Fed Lausanne DESL Lausanne Switzerland

ISBN: (纸本)9781467356688

Energy balance and ancillary services provided by distributed storage systems to active distribution networks represent two aspects of a single problem that needs to be properly treated in view of the typical distribution networks parameters. In this context, the paper focuses on the problem of the optimal siting and sizing of distributed storage systems. In particular, the paper proposes the formulation of a problem that accounts: (i) the voltage support of storage systems to the grid, (ii) the network losses and (iii) the cost of the energy-flow towards the external grid. As the formulated problem is mixed-integer, non-convex and non-linear, its solution requires the adoption of heuristic techniques. In this respect, a two-stage iterative procedure is proposed. The first stage of the procedure utilizes a genetic algorithm to provide locations and sizes of the distributed storage systems;the second stage evaluates the fitness of the solution provided by the first part by solving a daily AC optimal power flow. An application example, referring to the IEEE 13 busses test feeder, is included in order to demonstrate and discuss the efficiency of the proposed method.

关键词： IEEE standards concave programming distributed power generation distribution networks genetic algorithms integer programming iterative methods nonlinear programming

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SAR Canonical Feature Extraction using Molecule Dictionaries

SAR Canonical Feature Extraction using Molecule Dictionaries

引用

IEEE Radar Conference (RADAR)

作者： Hammond, G. Barry Jackson, Julie Ann Air Force Inst Technol Dept Elect & Comp Engn Wright Patterson AFB OH 45433 USA

ISBN: (纸本)9781467357944;9781467357920

We apply a molecule dictionary approach to synthetic aperture radar canonical feature extraction. These canonical features capture physically-relevant scattering geometry as a function of shape type, frequency, aspect, and polarization. The extraction problem is a nonlinear nonconvex optimization that includes model order selection, feature classification, and parameter estimation. Previous work used image-based initializations, gradient descent, and a hierarchical classification scheme to extract the features. The dictionary approach shifts much of the computational burden to dictionary formation which can be done offline, prior to feature extraction. We show results for cases when the true feature lies in the dictionary and when it does not. Discussion of the practical challenges of dictionary construction is given in the context of recent sparse recovery literature.

关键词： concave programming electromagnetic wave polarisation electromagnetic wave scattering feature extraction geometry image classification nonlinear programming parameter estimation radar imaging synthetic aperture radar

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Optimum Transmission through the Gaussian Multiple Access Channel

Optimum Transmission through the Gaussian Multiple Access Ch...

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IEEE International Symposium on Information Theory (ISIT)

作者： Calabuig, Daniel Gohary, Ramy Yanikomeroglu, Halim Univ Politecn Valencia Inst Telecommun & Multimedia Applicat E-46022 Valencia Spain Carleton Univ Dept Syst & Comp Engn Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9781479904464

In this paper we study the optimality of particular points in the capacity region of Gaussian multiple access channels (GMACs) with various power constraints. The points of interest maximize general rate objectives that arise in practical communication scenarios. Achieving these points constitutes the task of jointly optimizing time-sharing parameters, input covariance matrices and the order of decoding used by the successive interference cancellation receiver. To approach this problem Caratheodory's theorem is invoked to represent time-sharing and decoding orders jointly as a finite-dimensional matrix variable. This variable enables us to use variational inequalities to extend results pertaining to problems with linear objectives to more general, potentially nonconvex, problems. In particular, it is shown that for arbitrary objectives, if the power constraints are convex, it suffices for each user to use only one covariance matrix in all its allocated time slots. On the other hand, for arbitrary power constraints, if the objective is linear no time-sharing is necessary. These results significantly reduce the design complexity and render optimal signalling over GMAC more amenable to implementation in various practical scenarios.

关键词： Gaussian channels channel capacity concave programming covariance matrices decoding interference suppression multi-access systems radio receivers

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