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Periodic resource model for compositional real-time guarantees

Periodic resource model for compositional real-time guarante...

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Real-Time Systems Symposium (RTSS)

作者： Insik Shin Insup Lee Department of Computer and Information Science University of Pennsylvania Philadelphia PA USA

ISBN: (纸本)0769520448

We address the problem of providing compositional hard real-time guarantees in a hierarchy of schedulers. We first propose a resource model to characterize a periodic resource allocation and present exact schedulability conditions for our proposed resource model under the EDF and RM algorithms. Using the exact schedulability conditions, we then provide methods to abstract the timing requirements that a set of periodic tasks demands under the EDF and RM algorithms as a single periodic task. With these abstraction methods, for a hierarchy of schedulers, we introduce a composition method that derives the timing requirements of a parent scheduler from the timing requirements of its child schedulers in a compositional manner such that the timing requirement of the parent scheduler is satisfied, if and only if the timing requirements of its child schedulers are satisfied.

关键词： Processor scheduling Timing Scheduling algorithm Resource management Information science Algorithm design and analysis Computer interfaces Real time systems partitioning algorithms

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Localized watermarking: methodology and application to template mapping

Localized watermarking: methodology and application to templ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： D. Kirovski M. Potkonjak Computer Science Department University of California Los Angeles USA

The semiconductor industry has adopted the intellectual property (IP) business model as a dominant system-on-chip development platform. Since copyright fraud has been recognized as the most devastating obstruction to this model, a number of techniques for IP protection have been introduced. Most of them rely on a selection of a global solution to an optimization problem according to a unique user-specific digital signature. Although such techniques may provide convincing proof of authorship with little hardware overhead, they fail to protect design partitions, do not provide an easy procedure for watermark detection, and are not capable of detecting the watermark when the design or its part is augmented in another larger design. Since these demands are of the highest interest for the IP business, we introduce localized watermarking as an IP protection technique which enables these features while satisfying the demand for low-cost and transparency. We have applied the new watermarking technology to template mapping, a behavioral synthesis task. This watermarking method has been tested on a set of real-life benchmarks where high likelihood of authorship has been achieved with negligible overhead in solution quality.

关键词： Watermarking Protection Algorithm design and analysis partitioning algorithms Application software Digital signatures Constraint optimization Design optimization Computer science Electronics industry

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Grid Clustering Algorithm with Simple Leaping Search Technique

Grid Clustering Algorithm with Simple Leaping Search Techniq...

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International Symposium on Computer, Consumer and Control (IS3C)

作者： Cheng-Fa Tsai Jun-Hao Zhang Department of Management Information Systems National Pingtung University of Science and Technology Ping Tung Taiwan

Data mining is a critical data analysis technique for extracting hidden information from large databases for business or industrial applications. As the size of organizational databases increase, finding information and knowledge efficiently is essential. In the past, numerous clustering algorithms based on grid-clustering schemes have been proposed. This study proposes, simple-leaping search (SLS), a new grid-based clustering algorithm that partitions the space by the number of grids. It then sequentially searches odd columns of all grids according to the minimal point set at each grid. Based on whether the grid is useful or useless, different neighbor grids are searched. Experimental results show that the SLS clustering algorithm performs better than other clustering algorithms such as DBSCAN, IDBSCAN and GOD-CS.

关键词： Clustering algorithms partitioning algorithms Noise Algorithm design and analysis Data mining Spatial databases

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ComFu: Improving Visual Clustering by Commonality Fusion

ComFu: Improving Visual Clustering by Commonality Fusion

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International Conference on Machine Learning and Applications (ICMLA)

作者： Chunchun Li Manuel Günther Terrance E. Boult UCCS Colorado Springs USA UZH Zürich Switzerland

ISBN: (纸本)9781665443388

Clustering has a long history in the computer vision community with a myriad of applications. Clustering is a family of unsupervised machine learning techniques that group samples based on similarity. Multiple ad hoc techniques have been developed to combine or fuse clustering algorithms with dozens of different clustering techniques. This paper presents a new formalization of clustering fusion and introduces the novel Commonality Fusion (ComFu) technique to combine the advantages of different clustering algorithms by fusing their results on datasets. ComFu builds a pairwise commonality matrix of samples by computing how many clustering algorithms group each pair together. Using this matrix, ComFu builds initial clusters of points with high commonality and then assigns points with low commonality to clusters with the highest average commonality to those points with an automatic distance measure selection process. We start experiments by comparing ComFu with the prior state-of-the-art cluster fusion algorithms on eight UCI datasets. We then evaluate ComFu on practical vision clustering problems, advancing the state-of-the-art on a wide range of applications including clustering faces in the IJB-B dataset. We apply ComFu to fuse FINCH, the state-of-the-art ”parameter-free” approach, which returns multiple partitions and can use multiple distance metrics, and show that ComFu improves their result by fusing over metrics and partitions.

关键词： Measurement Visualization Machine learning algorithms Fuses Clustering algorithms Machine learning partitioning algorithms

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SoPC Architecture for a Key Point Detector

SoPC Architecture for a Key Point Detector

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International Conference on Field Programmable Logic and Applications

作者： H. Djakou Chati F. Muhlbauer T. Braun C. Bobda K. Berns Self-Organizing Embedded System Group Robotic Research Lab Kaiserslautern University of Technology Germany Self-Organizing Embedded System Group Kaiserslautern University Germany

The design and implementing of a key point detector on embedded reconfigurable hardware is investigated. The major challenges are efficient hardware/software partitioning of the key point detector algorithm, data flow management as well as efficient use of memory, bus and processor. We present a modular and manual hardware/software co-design, with its implementation on a Xilinx XUP-Virtex II Pro board to solve these issues.

关键词： Hardware Detectors Robots Signal processing algorithms Embedded system partitioning algorithms Object detection Navigation Digital signal processing chips Field programmable gate arrays

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Geodesics and an optimal control algorithm

Geodesics and an optimal control algorithm

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IEEE Conference on Decision and Control

作者： C.Y. Kaya J.L. Noakes School of Mathematics University of South Australia SA Australia Department of Mathematics University of Western Australia Nedlands WA Australia

A global algorithm for finding a geodesic joining given two points on a Riemannian manifold has recently been developed. It is simple to implement, and works well in practice, with no need for an initial guess. An optimal control problem is much more general than finding a geodesic. Nevertheless, a generalization seems now possible, based on recent numerical experiments.

关键词： Optimal control partitioning algorithms Mathematics Control systems Australia Feedback Equations Quadratic programming Spline Boundary conditions

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Efficient regular data structures and algorithms for location and proximity problems

Efficient regular data structures and algorithms for locatio...

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Annual IEEE Symposium on Foundations of Computer Science

作者： A. Amir A. Efrat P. Indyk H. Samet IBM Almaden Research Center San Jose CA USA Computer Science Department University of Stanford USA Computer Science Department University of Maryland College Park MD USA

Investigates data structures obtained by a recursive partitioning of the input domain into regions of equal size. One of the most well-known examples of such a structure is the quadtree, which is used in this paper as a basis for more complex data structures; we also provide multidimensional versions of the stratified tree of P. van Emde Boas (1997). We show that, under the assumption that the input points have limited precision (i.e. are drawn from an integer grid of size u), these data structures yield efficient solutions to many important problems. In particular, they allow us to achieve O(log log u) time per operation for finding the dynamic approximate nearest neighbor (under insertions and deletions) and the exact online closest pair (under insertions only) in any constant dimension. They allow O(log log u) point location in a given planar shape or in its expansion (dilation by a ball of a given radius). Finally, we provide a linear-time (optimal) algorithm for computing the expansion of a shape represented by a quadtree. This result shows that the spatial order imposed by this regular data structure is sufficient to optimize the dilation by a ball operation.

关键词： Data structures Shape Computer science Tree data structures Multidimensional systems partitioning algorithms Nearest neighbor searches Educational institutions Contracts Data processing

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Two-dimensional Clustering-based Discriminant Analysis for SAR ATR

Two-dimensional Clustering-based Discriminant Analysis for S...

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Li-ping Hu Hong-wei Liu Kui-ying Yin Shun-jun Wu National Laboratory o f Radar Signal Processing Xidian University Xi'an Shanxi China

This paper gives a new image feature extraction technique coined two-dimensional clustering-based discriminant analysis (2DCDA), which is based on 2D image matrices for constructing the scatter matrices and assumes that the data obeys the multimodal distribution. The detailed procedure of 2DCDA is to first partition each class of the data into multiple clusters via fast 2D global k-means clustering algorithm, and then try to find some directions such that the projections of every pair of clusters from different classes are well separated while the within-cluster scatter is minimized. Therefore, it fully exploits the cluster information and alleviates the linearly unseparable problem to some extent. According to the projection fashion, we divide 2DCDA into two versions, the right 2DCDA (R-2DCDA) and the left 2DCDA (L-2DCDA). They compress the image row or column only, so they need more features. To solve this problem, two-directional 2DCDA ((2D) 2 CDA) is developed, which compresses the image row and column simultaneously. Experiments have been carried out for recognition of three types of ground vehicles in the Moving and Stationary Target Acquisition and Recognition (MSTAR) public database to evaluate and compare the performances of the proposed algorithms with other methods. Results demonstrate that 2DCDA and (2D) 2 CDA are effective. And, the highest recognition rate is up to 97.89%, which is the best ever reported in the literatures.

关键词： Scattering Image coding Target recognition Feature extraction Image analysis Clustering algorithms partitioning algorithms Land vehicles Image databases Spatial databases

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Coverage control by robotic networks with limited-range anisotropic sensory

Coverage control by robotic networks with limited-range anis...

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2008 American Control Conference (ACC), vol.7

作者： Katie Laventall Jorge Cortes Aeronautics and Astronautics Department University of Stanford Stanford CA USA Department of Mechanical and Aerospace Engineering University of California San Diego CA USA

This paper considers the deployment of a network of robotic agents with limited-range communication and anisotropic sensing capabilities. We encode the environment coverage provided by the network by means of an expected-value objective function. This function has a gradient which is not amenable to distributed computation. We provide a constant-factor approximation of this measure via an alternative aggregate objective function whose gradient is spatially distributed over the limited-range Delaunay proximity graph. We characterize the smoothness properties of the aggregate expected-value function and propose a distributed deployment algorithm to optimize it. Simulations illustrate the results.

关键词： Robot control Robot sensing systems Anisotropic magnetoresistance Robot kinematics Aggregates partitioning algorithms Communication system control Distributed computing Computational modeling Computational geometry

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Multi-reference neighborhood search for vector quantization by neural network prediction and self-organized feature map

Multi-reference neighborhood search for vector quantization ...

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International Conference on Neural Networks

作者： K.W. Chan K.L. Chan Department of Electronic Engineeering City University of Hong Kong Kowloon Hong Kong China

Reference neighbor search (RNS) is a new technique for fast searching of vector quantization (VQ). However, the optimal performance is not guaranteed and the performance is greatly affected by the selection of reference point. In this research, the authors employed the Kohonen self organized feature map to generate a codebook of high degree of neighborhood and multi-layer perceptron (MLP) neural network to adaptively predict the reference. The predicted reference is closer to the input, thus the search distance will be reduced together with multiple queues and a look up table, the number of searches is significantly reduced while maintaining optimal performance.

关键词： Vector quantization Neural networks Discrete cosine transforms Nearest neighbor searches Image coding Pixel Image segmentation partitioning algorithms Nonlinear distortion Distortion measurement

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