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28th Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

作者： Aghdam, Sina Rezaei Duman, Tolga M. Bilkent Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey

ISBN: (纸本)9781538635315

We propose transmit optimization techniques for multi-input multi-output (MIMO) wiretap channels with statistical channel state information (CSI) at the transmitter. We consider doubly correlated channels towards the legitimate receiver and the eavesdropper. The aim is to maximize the secrecy rates using the knowledge of the channel correlation matrices. We develop gradient-descent based optimization algorithms for obtaining the optimal transmit signals for both Gaussian and finite-alphabet inputs. Furthermore, we introduce a joint precoder and artificial noise (AN) design scheme. We demonstrate the efficacy of the proposed schemes via numerical examples.

关键词： Optimization Receivers Transmitters algorithm design and analysis Covariance matrices Correlation Signal design

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algorithmic models of human decision making in Gaussian multi-armed bandit problems 13

Algorithmic models of human decision making in Gaussian mult...

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13th European Control Conference (ECC)

作者： Reverdy, Paul Srivastava, Vaibhav Leonard, Naomi E. Princeton Univ Dept Mech & Aerosp Engn Princeton NJ 08544 USA

ISBN: (纸本)9783952426913

We consider a heuristic Bayesian algorithm as a model of human decision making in multi-armed bandit problems with Gaussian rewards. We derive a novel upper bound on the Gaussian inverse cumulative distribution function and use it to show that the algorithm achieves logarithmic regret. We extend the algorithm to allow for stochastic decision making using Boltzmann action selection with a dynamic temperature parameter and provide a feedback rule for tuning the temperature parameter such that the stochastic algorithm achieves logarithmic regret. The stochastic algorithm encodes many of the observed features of human decision making.

关键词： algorithm design and analysis Bayes methods Decision making Equations Heuristic algorithms Random variables Stochastic processes algorithm design and analysis Heuristic algorithms Bayes methods Random variable Markov chain decision making Stochastic Processes Gauss

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An Efficient Backtracking-based Approach to Turn-constrained Path Planning for Aerial Mobile Robots

An Efficient Backtracking-based Approach to Turn-constrained...

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European Conference on Mobile Robots (ECMR)

作者： Sharma, Hrishikesh Sebastian, Tom Balamuralidhar, P. Tata Consultancy Serv Ltd Embedded Syst & Robot Res Lab Bombay Maharashtra India

ISBN: (纸本)9781538610961

Many important classes of civilian applications of Unmanned Aerial Vehicles, such as the class of remote monitoring of long linear infrastructures e.g. power grid, gas pipeline etc. entail usage of fixed-wing vehicles. Such vehicles are known to be constrained with restricted angular movement. Similarly, mobile robots such as car robots or tractor-trailer robots are also known to entail such constraint. The algorithms known so far require a lot of preprocessing for turn constraint. In this paper, we introduce a novel algorithm for turn angle-constrained path planning. The proposed algorithm uses a greedy backtracking strategy to satisfy the constraint, which minimizes the amount of backtracking involved. By further constructing an efficient depth-first brute-force algorithm for path planning and comparing against its performance, we see an improvement in convergence performance by a factor of at least 10x. Further, compared to recent LIAN suite of path-planning algorithm, our algorithm exhibits much reduced discretization offset/error with respect to shortest path length. We believe that this algorithm will form an useful stepping stone towards evolution of better path planning algorithm for specific mobile robots such as UAVs.

关键词： algorithm design and analysis Path planning Planning Turning Unmanned aerial vehicles Two dimensional displays Approximation algorithms

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A Novel Power Flow algorithm for AC Microgrids Based on Time Domain Iteration 43

A Novel Power Flow Algorithm for AC Microgrids Based on Time...

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43rd Annual Conference of the IEEE-Industrial-Electronics-Society (IECON)

作者： Zhu, Yixin Wang, Tao Xiong, Liansong Yang, Ping Xu, ZhiRong Jiangnan Univ Inst Automat Wuxi Peoples R China Nanjing Inst Technol Sch Automat Nanjing Jiangsu Peoples R China South China Univ Technol Sch Elect Power Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781538611272

To manage the microgrid effectively, it is important to get the power information among multiple distributed generation (DG) units. However, when the droop control method is adopted, as the corresponding DG units cannot be simply modeled as VF or PQ buses, the conventional power flow algorithm may become inapplicable. To solve this issue, a time domain iteration (TDI) based power flow algorithm is hereby proposed. Firstly, a microgrid model is prepared, containing a network model and several DG unit models. Then, the proposed TDI is executed for power flow calculation, which mimics the real-time operation of microgrids. In each iteration, the DG unit models input voltages and currents to the network model;then the network model changes its state accordingly and feeds related parameters back to those DG unit models. As the DG unit models simulate the behavior of actual DG units, the proposed algorithm is not limited to the droop control governed microgrids. Moreover, as the TDI has definite physical meaning, convergence problems can be avoided. Finally, the validity of the proposed power flow algorithm is verified through the Matlab simulation results from an 8 -bus microgrid system.

关键词： Microgrids Mathematical model Voltage control Reactive power algorithm design and analysis Load modeling Time-domain analysis

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Cloud-distributed computational experiments for combinatorial optimization 40

Cloud-distributed computational experiments for combinatoria...

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40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Brcic, Mario Hlupic, Nikica Fac Elect Engn & Comp Zagreb Croatia

ISBN: (纸本)9789532330922

The development of optimization algorithms for combinatorial problems is a complicated process, both guided and validated by the computational experiments over the different scenarios. Since the number of experiments can be very large and each experiment can take substantial execution time, distributing the load over the cloud speeds up the whole process significantly. In this paper we present the system used for experimental validation and comparison of stochastic combinatorial optimization algorithms, applied in the specific case of project scheduling problems.

关键词： Databases Optimization Cloud computing algorithm design and analysis Computer architecture Scheduling Tools

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Group Marching Tree: Sampling-Based Approximately Optimal Motion Planning on GPUs 1

Group Marching Tree: Sampling-Based Approximately Optimal Mo...

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1st IEEE International Conference on Robotic Computing (IRC)

作者： Ichter, Brian Schmerling, Edward Pavone, Marco Stanford Univ Aeronaut & Astronaut Stanford CA 94305 USA Stanford Univ Inst Computat & Math Engn Stanford CA 94305 USA

ISBN: (纸本)9781509067244

This paper presents a novel approach, named the Group Marching Tree (GMT*) algorithm, to planning on GPUs at rates amenable to application within control loops, allowing planning in real-world settings via repeated computation of near-optimal plans. GMT*, like the Fast Marching Tree (FMT*) algorithm, explores the state space with a "lazy" dynamic programming recursion on a set of samples to grow a tree of near-optimal paths. GMT*, however, alters the approach of FMT* with approximate dynamic programming by expanding, in parallel, the group of all active samples with cost below an increasing threshold, rather than only the minimum cost sample. This group approximation enables low-level parallelism over the sample set and removes the need for sequential data structures, while the "lazy" collision checking limits thread divergence-all contributing to a very efficient GPU implementation. While this approach incurs some suboptimality, we prove that GMT* remains asymptotically optimal up to a constant multiplicative factor. We show solutions for complex planning problems under differential constraints can be found in similar to 10 ms on a desktop GPU and similar to 30 ms on an embedded GPU, representing a significant speed up over the state of the art, with only small losses in performance. Finally, we present a scenario demonstrating the efficacy of planning within the control loop (similar to 100 Hz) towards operating in dynamic, uncertain settings.

关键词： Planning Dynamic programming Graphics processing units Heuristic algorithms Parallel processing algorithm design and analysis Trajectory

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Sparse Density Estimation on Multinomial Manifold Combining Local Component analysis

Sparse Density Estimation on Multinomial Manifold Combining ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Hong, Xia Gao, Junbin Univ Reading Sch Syst Engn Reading RG6 6AY Berks England Charles Sturt Univ Sch Comp & Math Bathurst NSW 2795 Australia

ISBN: (纸本)9781479919598

A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion combining local component analysis for the finite mixture model. We start with a Parzen window estimator which has the Gaussian kernels with a common covariance matrix, the local component analysis is initially applied to find the covariance matrix using expectation maximization algorithm. Since the constraint on the mixing coefficients of a finite mixture model is on the multinomial manifold, we then use the well-known Riemannian trust-region algorithm to find the set of sparse mixing coefficients. The first and second order Riemannian geometry of the multinomial manifold are utilized in the Riemannian trust-region algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with competitive accuracy to existing kernel density estimators.

关键词： algorithm design and analysis Kernel Manifolds

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Improvement and Implementation of Quine-McCluskey algorithm for Synthesis of Reversible Logic Circuits 2

Improvement and Implementation of Quine-McCluskey Algorithm ...

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2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： Shuguang Zhao Chaozheng Wang Junling Sun College of Information Science and Technology Donghua University

In order to meet the requirements of the reversible logic synthesis, the Quine-McCluskey algorithm is improved and Implemented in this paper. By analyzing the difference and relation between the "SOP"

ISBN: (纸本)9781467389808

关键词： algorithm design and analysis Logic circuits Logic gates Logic functions Quantum computing Sun Information science

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Situation Assessment Using Cellular Automata Paradig

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IEEE Aerospace and Electronic Systems Magazine 1992年第1期7卷 32-37页

作者： Glickstein, Ira Stiles, Peter IBM Federal Sector Division Owego NY United States

The cellular automata (CA) concept is introduced, and it is shown how it is applied to situation assessment in connection with digital map-based tasks. The demonstration system makes use of 11480 virtual processors. Although the use of the CA paradigm was motivated by projections of future availability of massively parallel hardware, the CA algorithms have run efficiently on ordinary serial computers.

关键词： Parallel processing Routing Hardware design engineering Power engineering and energy Artificial intelligence algorithm design and analysis Crops Concurrent computing Testing

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Scalable Sparse Tensor Decompositions in Distributed Memory Systems 15

Scalable Sparse Tensor Decompositions in Distributed Memory ...

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International Conference for High Performance Computing, Networking, Storage and analysis (SC)

作者： Kaya, Oguz Ucar, Bora INRIA Rocquencourt France UCB Lyon 1 CNRS ENS Lyon UMR 5668InriaENS LyonLIP Lyon France CNRS F-75700 Paris France

ISBN: (纸本)9781450337236

We investigate an efficient parallelization of the most common iterative sparse tensor decomposition algorithms on distributed memory systems. A key operation in each iteration of these algorithms is the matricized tensor times Khatri-Rao product (MTTKRP). This operation amounts to element-wise vector multiplication and reduction depending on the sparsity of the tensor. We investigate a fine and a coarse-grain task definition for this operation, and propose hypergraph partitioning-based methods for these task definitions to achieve the load balance as well as reduce the communication requirements. We also design a distributed memory sparse tensor library, HyperTensor, which implements a well-known algorithm for the CANDECOMP/ PARAFAC (CP) tensor decomposition using the task definitions and the associated partitioning methods. We use this library to test the proposed implementation of MTTKRP in CP decomposition context, and report scalability results up to 1024 MPI ranks. We observed up to 194 fold speedups using 512 MPI processes on a well-known real world data, and significantly better performance results with respect to a state of the art implementation.

关键词： Tensile stress algorithm design and analysis Signal processing algorithms Computed tomography Sparse matrices Libraries Approximation algorithms

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