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Efficient robust Broadband Beamforming algorithms Using Variable Loading

IEEE LATIN AMERICA TRANSACTIONS 2012年第3期10卷 1697-1702页

作者： Hossain, M. S. Godara, L. C. Islam, M. R. Australiano Def Force Acad Univ New S Walies Canberra ACT Australia

Steering angle errors are known to be a major cause of performance degradation of adaptive beamformers, especially when the signal of interest is present in the measurements. Diagonal loading is one of the most widely used and effective methods to improve robustness of adaptive beamformers. This paper presents two robust beamforming algorithms using efficient realisation techniques. The techniques do not use a pre-steered array and allow an array designer to specify the frequency response of the processor in the look direction and steered the main beam of specified frequency response in an arbitrary direction. The proposed techniques are computationally efficient. The techniques used in the paper extend two previously published techniques used for narrow band beamforming to broadband beamforming. Simulation results exhibit enhanced robustness performance of the broadband beamformer.

关键词： smart antennas broadband beamforming robust algorithms efficient realisation technique

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Achieving robust wireless localization resilient to signal strength attacks

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WIRELESS NETWORKS 2012年第1期18卷 45-58页

作者： Li, Xiaoyan Chen, Yingying Yang, Jie Zheng, Xiuyuan Lafayette Coll Dept Comp Sci Easton PA 18042 USA Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA

Received signal strength (RSS) based algorithms have been very attractive for localization since they allow the reuse of existing communication infrastructure and are applicable to many commodity radio technologies. Such algorithms, however, are sensitive to a set of non-cryptographic attacks, where the physical measurement process itself can be corrupted by adversaries. For example, the attacker can perform signal strength attacks by placing an absorbing or reflecting material around a wireless device to modify its RSS readings. In this work, we first formulate the all-around signal strength attacks, where similar attacks are launched towards all landmarks, and experimentally show the feasibility of launching such attacks. We then propose a general principle for designing RSS-based algorithms so that they are robust to all-around signal strength attacks. To evaluate our approach, we adapt a set of representative RSS-based localization algorithms according to our principle. We experiment with both simulated attacks and two sets of real attack scenarios. All the experiments show that our design principle can be applied to a wide spectrum of algorithms to achieve comparable performance with much better robustness.

关键词： Wireless localization Signal strength attacks robust algorithms Design principle

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robust Ranking Models via Risk-Sensitive Optimization 12

Robust Ranking Models via Risk-Sensitive Optimization

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35th ACM SIGIR Annual International Conference on Research and Development in Information Retrieval

作者： Wang, Lidan Bennett, Paul N. Collins-Thompson, Kevyn Univ Maryland Dept Comp Sci College Pk MD 20742 USA Microsoft Res Redmond WA USA

ISBN: (纸本)9781450316583

Many techniques for improving search result quality have been proposed. Typically, these techniques increase average effectiveness by devising advanced ranking features and/or by developing sophisticated learning to rank algorithms. However, while these approaches typically improve average performance of search results relative to simple baselines, they often ignore the important issue of robustness. That is, although achieving an average gain overall, the new models often hurt performance on many queries. This limits their application in real-world retrieval scenarios. Given that robustness is an important measure that can negatively impact user satisfaction, we present a unified framework for jointly optimizing effectiveness and robustness. We propose an objective that captures the tradeoff between these two competing measures and demonstrate how we can jointly optimize for these two measures in a principled learning framework. Experiments indicate that ranking models learned this way significantly decreased the worst ranking failures while maintaining strong average effectiveness on par with current state-of-the-art models.

关键词： Re-ranking robust algorithms machine learning

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Analytical aspects of tie breaking

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THEORETICAL COMPUTER SCIENCE 2012年 465卷 1-9页

作者： Jacobs, Tobias Natl Inst Informat Principles Informat Div Tokyo Japan

This article describes an analytical framework for reasoning about the issue of tie breaking in algorithm theory. The core of this framework is the concept of robust algorithms. Such kind of algorithms have the convenient property that an arbitrary set of degenerate cases can be ignored without loss of generality during proofs of many important properties, e.g.. runtime, space requirements, feasibility, competitive and approximation ratios. Here degeneracy is defined as a set of problem instances satisfying a certain property, and this property is independent from both the algorithm under consideration and the specific combinatorial problem structure. It turns out that robustness is related to the tie breaking policy of algorithms in two different ways. On the one hand, the set of inputs where a tie actually occurs is typically (but not always) a degenerate case. On the other hand, we show that for any algorithm there is a way to break ties such that it becomes robust. In particular, robustness is guaranteed by any tie breaking strategy that can be interpreted as symbolic perturbation. For many typical algorithms the implicit usage of symbolic perturbation can be easily verified and so the consideration of degenerate cases can be avoided during their analysis. The concept of robustness also gives a theoretical explanation of why tie breaking does often not matter at all. (c) 2012 Elsevier B.V. All rights reserved.

关键词： Perturbation robust algorithms Proof technique Degeneracy

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robust EXTRACTION OF STATISTICS FROM IMAGES OF MATERIAL FRAGMENTATION

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INTERNATIONAL JOURNAL OF IMAGE AND GRAPHICS 2011年第3期11卷 377-401页

作者： Kamath, Chandrika Hurricane, Omar A. Lawrence Livermore Natl Lab Livermore CA 94551 USA Univ Calif Los Angeles Inst Plasma & Fus Res Los Angeles CA 90024 USA

The extraction of statistics of interest in experimental or observational images is often challenging due to the noise in the data and the variation across images in a dataset. For an objective analysis, any algorithms used must be relatively insensitive to the choice of parameters. In addition, to avoid manual analysis, which is tedious and error-prone, these algorithms must also lend themselves to full or partial automation, especially when the number of images is large. In this paper, we describe the use of image analysis techniques to extract various statistics from experimental images resulting from the fragmentation of materials. We show how we can use a sequence of relatively simple algorithms to provide a robust solution for the extraction of statistics on the fragments and the gaps between them.

关键词： Fragmentation of materials image enhancement segmentation feature extraction robust algorithms

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On the limitations of classical benchmark functions for evaluating robustness of evolutionary algorithms

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APPLIED MATHEMATICS AND COMPUTATION 2010年第9期215卷 3222-3229页

作者： Ahrari, Ali Saadatmand, Mohammad R. Shariat-Panahi, Masoud Atai, Ali A. Univ Tehran Fac Engn Dept Mech Engn Tehran Iran Mobile Commun Co Iran Tehran Iran

Although evolutionary algorithms (EAs) have some operators which let them explore the whole search domain, still they get trapped in local minima when multimodality of the objective function is increased. To improve the performance of EAs, many optimization techniques or operators have been introduced in recent years. However, it seems that these modified versions exploit some special properties of the classical multimodal benchmark functions, some of which have been noted in previous research and solutions to eliminate them have been proposed. In this article, we show that quite symmetric behavior of the available multimodal test functions is another example of these special properties which can be exploited by some EAs such as covariance matrix adaptation evolution strategy (CMA-ES). This method, based on its invariance properties and good optimization results for available unimodal and multimodal benchmark functions, is considered as a robust and efficient method. However, as far as black box optimization problems are considered, no special trend in the behavior of the objective function can be assumed;consequently this symmetry limits the generalization of optimization results from available multimodal benchmark functions to real world problems. To improve the performance of CMA-ES, the Elite search sub-algorithm is introduced and implemented in the basic algorithm. Importance and effect of this modification is illustrated experimentally by dissolving some test problems in the end. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Black box optimization Elite search process robust algorithms Generalization of optimization results Multimodal functions Symmetric behavior

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A Dynamic Data Middleware Cache for Rapidly-Growing Scientific Repositories

A Dynamic Data Middleware Cache for Rapidly-Growing Scientif...

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11th International Middleware Conference

作者： Malik, Tanu Wang, Xiaodan Little, Philip Chaudhary, Amitabh Thakar, Ani Purdue Univ Cyber Ctr W Lafayette IN 47907 USA Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA Johns Hopkins Univ Dept Phys & Astron Baltimore MD 21218 USA Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9783642169540

Modern scientific repositories are growing rapidly in size. Scientists are increasingly interested in viewing the latest data as part of query results. Current scientific middleware cache systems, however, assume repositories are static. Thus, they cannot answer scientific queries with the latest data. The queries, instead, are routed to the repository until data at the cache is refreshed. In data-intensive scientific disciplines, such as astronomy, indiscriminate query routing or data refreshing often results in runaway network costs. This severely affects the performance and scalability of the repositories and makes poor use of the cache system. We present Delta a dynamic data middleware cache system for rapidly-growing scientific repositories. Delta's key component is a decision framework that adaptively decouples data objects choosing to keep some data object at the cache, when they are heavily queried, and keeping some data objects at the repository, when they are heavily updated. Our algorithm profiles incoming workload to search for optimal data decoupling that reduces network costs. It leverages formal concepts from the network flow problem, and is robust to evolving scientific workloads. We evaluate the efficacy of Delta, through a prototype implementation, by running query traces collected from a real astronomy survey.

关键词： dynamic data middleware cache network traffic vertex cover robust algorithms

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A dynamic data middleware cache for rapidly-growing scientific repositories 10

A dynamic data middleware cache for rapidly-growing scientif...

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Proceedings of the ACM/IFIP/USENIX 11th International Conference on Middleware

作者： Tanu Malik Xiaodan Wang Philip Little Amitabh Chaudhary Ani Thakar Purdue University Johns Hopkins University University of Notre Dame

ISBN: (纸本)9783642169540

Modern scientific repositories are growing rapidly in size. Scientists are increasingly interested in viewing the latest data as part of query results. Current scientific middleware cache systems, however, assume repositories are static. Thus, they cannot answer scientific queries with the latest data. The queries, instead, are routed to the repository until data at the cache is refreshed. In data-intensive scientific disciplines, such as astronomy, indiscriminate query routing or data refreshing often results in runaway network costs. This severely affects the performance and scalability of the repositories and makes poor use of the cache system. We present Delta a dynamic data middleware cache system for rapidly-growing scientific repositories. Delta's key component is a decision framework that adaptively decouples data objects---choosing to keep some data object at the cache, when they are heavily queried, and keeping some data objects at the repository, when they are heavily updated. Our algorithm profiles incoming workload to search for optimal data decoupling that reduces network costs. It leverages formal concepts from the network flow problem, and is robust to evolving scientific workloads. We evaluate the efficacy of Delta, through a prototype implementation, by running query traces collected from a real astronomy survey.

关键词： robust algorithms network traffic vertex cover dynamic data middleware cache

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robust Methods of Ellipsoidal Estimation of Dynamical Systems State under Restrictions on Noise of Output Measurements and Rate of their Variation

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JOURNAL OF AUTOMATION AND INFORMATION SCIENCES 2008年第10期40卷 38-46页

作者： Volosov, V. V. Shevchenko, V. N. Natl Acad Sci Ukraine Inst Space Res Kiev Ukraine Natl Space Agcy Ukraine Kiev Ukraine

We obtained new robust algorithms of ellipsoidal estimate of the vector of state of dynamical systems by the results of measurement of their outputs, which are distorted by additive noise. In contrast to known algorithms, which account only boundedness of noises, we additionally take into account boundedness of rate of their variation. Efficiency of the obtained algorithms is shown by results of computer modeling of their use in the problem of control of orbital spacecraft orientation.

关键词： robust algorithms ellipsoidal estimate vector of state of dynamical systems results of measurement of outputs additive noise bounded noises bounded rate of noises variation efficiency results of computer modeling problem of control of orbital spacecraft orientation

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robustness and applicability of Markov chain Monte Carlo algorithms for eigenvalue problems

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APPLIED MATHEMATICAL MODELLING 2008年第8期32卷 1511-1529页

作者： Dimov, I. T. Philippe, B. Karaivanova, A. Weihrauch, C. Univ Reading Ctr Adv Comp & Emerging Technol Reading RG6 6AH Berks England Bulgarian Acad Sci Dept Parallel Algorithms IPP BU-1113 Sofia Bulgaria Inst Natl Rech Informat & Automat IRISA F-35042 Rennes France

In this paper we analyse applicability and robustness of Markov chain Monte Carlo algorithms for eigenvalue problems. We restrict our consideration to real symmetric matrices. Almost Optimal Monte Carlo (MAO) algorithms for solving eigenvalue problems are formulated. Results for the structure of both - systematic and probability error are presented. It is shown that the values of both errors can be controlled independently by different algorithmic parameters. The results present how the systematic error depends on the matrix spectrum. The analysis of the probability error is presented. It shows that the close (in some sense) the matrix under consideration is to the stochastic matrix the smaller is this error. Sufficient conditions for constructing robust and interpolation Monte Carlo algorithms are obtained. For stochastic matrices an interpolation Monte Carlo algorithm is constructed. A number of numerical tests for large symmetric dense matrices are performed in order to study experimentally the dependence of the systematic error from the structure of matrix spectrum. We also study how the probability error depends on the balancing of the matrix. (c) 2007 Elsevier Inc. All rights reserved.

关键词： Monte Carlo algorithms Markov chain eigenvalue problem robust algorithms

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