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检索条件"主题词=partitioning algorithms"

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An active divide-and-conquer algorithm for sparse recovery support: Fluctuating targets case

An active divide-and-conquer algorithm for sparse recovery s...

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International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa)

作者： Marco La Manna Daniel Fuhrmann Department of Electrical and Computer Engineering Michigan Technological University Houghton MI

We introduce a novel sparse signal detection algorithm, whose goal is to localize an unknown number of fluctuating targets in a sparse scenario, for example composed by N target sites. Rather than probing each cell with standard detection techniques, we employ an adaptive, step-by-step, tree-structured algorithm, that iteratively narrows the set of possible candidate locations. More specifically, assume that the transmitter is able to illuminate partitions of the target space at time and that the receiver acquires noisy nonlinear measurements of the partitions. Based on a comparison between these measurements and a threshold, the algorithm decides which partitions may contain targets (and, thus, they need to be probed at the next step) and which should be immediately discarded (as targets may not be present). Results show that the described algorithm is able to determine the location of the targets with fairly low False Discovery Proportion (FDP) and decreasing Non Discovery Proportion (NDP), as the available budget energy allocated to the algorithm increases.

关键词： partitioning algorithms Transmitters Receivers Radar Noise measurement Support vector machines Compressed sensing

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Fair scheduling with QoS support in ad hoc networks

Fair scheduling with QoS support in ad hoc networks

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Conference on Local Computer Networks (LCN)

作者： Hsi-Lu Chao Jia-Chun Kuo Wanjiun Liao Department of Electrical Engineering National Taiwan University Taipei Taiwan

ISBN: (纸本)0769515916

The paper studies fair scheduling with quality of service (QoS) support in ad hoc networks. The goal is to satisfy the minimum bandwidth requirements of guaranteed flows and to provide a fair share of residual bandwidth among all flows. We propose a new cluster-based mechanism called two-tier slot allocation protocol (2TSAP), which improves system throughput and ensures per-cluster fairness while satisfying the requirements of guaranteed flows. With 2TSAP, the network is logically partitioned into clusters, each with a scheduler. The scheduler assigns time slots to mobiles in the affiliated clusters based on the first tier algorithm. The mobiles scheduled to send at the next time slot then in turn assign the time slot to flows determined by the second tier algorithm. We compare the performance of 2TSAP with Q EMLM-FQ, a virtual-time based fair scheduling mechanism with QoS support. The simulation results show that 2TSAP meets the minimum requirements of guaranteed flows, shares the residual bandwidth fairly among all flows, and improves overall system throughput.

关键词： Intelligent networks Ad hoc networks Quality of service Bandwidth Throughput Protocols Clustering algorithms partitioning algorithms Scheduling algorithm Wireless networks

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Sparsification-a technique for speeding up dynamic graph algorithms

Sparsification-a technique for speeding up dynamic graph alg...

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Annual IEEE Symposium on Foundations of Computer Science

作者： D. Eppstein Dept. of Inf. & Comput. Sci. California Univ. Irvine CA USA

The authors provide data structures that maintain a graph as edges are inserted and deleted, and keep track of the following properties: minimum spanning forests, best swap, graph connectivity, and graph 2-edge-connectivity, in time O(n/sup 1/2/log(m/n)) per change; 3-edge-connectivity, in time O(n/sup 2/3/) per change; 4-edge-connectivity, in time O(n alpha (n)) per change; k-edge-connectivity, in time O(n log n) per change; bipartiteness, 2-vertex-connectivity, and 3-vertex-connectivity, in time O(n log(m/n)) per change; and 4-vertex-connectivity, in time O(n log(m/n)+n alpha (n)) per change. Further results speed up the insertion times to match the bounds of known partially dynamic algorithms. The algorithms are based on a technique that transforms algorithms for sparse graphs into ones that work on any graph, which they call sparsification.< >

关键词： Heuristic algorithms Data structures Computer science Tree graphs Algorithm design and analysis partitioning algorithms Binary trees

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Context-sensitive automatic categorization of web database query results

Context-sensitive automatic categorization of web database q...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Xiangfu Meng Jinguang Sun Chunxiao Liu School of Electronic and Information Engineering Liaoning Technical University Huludao China College of Electronics and Information Engineering Liaoning University of Technology Jinzhou China

To deal with the problem of too many answers returned from a Web database in response to a user query, this paper proposes a novel categorization approach which takes advantages of the user contextual preferences to construct a navigational tree in order to reduce the information overload. Based on the user original query, we first speculate how much the user cares about each attribute in the specified context and assign a corresponding weight to it. Then, the categorizing attribute in each level of the tree can be determined according to the weight of the attribute. The categorizing attribute for the first level of the tree is the attribute with the maximum weight. Next, we use the histogram construction algorithm to partition the values of each categories of the tree, the category with the larger exploring probability will be provided earlier to the user. Finally, the navigational tree is generated automatically and presented to the user, such that the user can easily select the relevant tuples matching his needs. Results of a preliminary user study demonstrate that our categorization method can capture the user's preferences effectively.

关键词： Navigation Databases Histograms Clustering algorithms Context Construction industry partitioning algorithms

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Texture Segmentation using Ant Tree Clustering

Texture Segmentation using Ant Tree Clustering

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IEEE International Conference on Engineering of Intelligent Systems, ICEIS

作者： A.H. Channa N.M. Rajpoot K.M. Rajpoot Faculty of Computer Science & Engineering GIK Institute of Engineering Science and Technology Pakistan Department of Computer Science University of Warwick UK

Motivated by the self-assembling behavior of real ants, we present a novel algorithm for texture segmentation which is based on ant tree clustering of wavelet features. In a pattern recognition setting, wavelet features are extracted using either of the two subband filtering methods: discrete wavelet transform (DWT) or discrete wavelet packet transform (DWPT). The feature classification process is inspired by the self-assembling behavior observed in real ants where ants progressively become attached to an existing support and then successively to other attached ants thus building trees based on the similarity of feature vectors. The results thus obtained compare favorably to those of other recently published filtering based texture segmentation algorithms

关键词： Discrete wavelet transforms Clustering algorithms Image texture analysis partitioning algorithms Computer science Algorithm design and analysis Feature extraction Filtering Image segmentation Wavelet analysis

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The sparse cyclic distribution against its dense counterparts

The sparse cyclic distribution against its dense counterpart...

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International Symposium on Parallel Processing

作者： G. Bandera M. Ujaldon M.A. Trenas E.L. Zapata Computer Architecture Department University of Malaga Spain

Several methods have been proposed in the literature for the distribution of data on distributed memory machines, either oriented to dense or sparse structures. Many of the real applications, however, deal with both kinds of data jointly. The paper presents techniques for integrating dense and sparse array accesses in a way that optimizes locality and further allows an efficient loop partitioning within a data-parallel compiler. The approach is evaluated through an experimental survey with several compilers and parallel platforms. The results prove the benefits of the BRS sparse distribution when combined with CYCLIC in mixed algorithms and the poor efficiency achieved by well-known distribution schemes when sparse elements arise in the source code.

关键词： Sparse matrices Character generation Computer architecture Scattering Iterative algorithms Application software Optimizing compilers partitioning algorithms Program processors Distributed computing

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Electricity price forecasting using a clustering approach

Electricity price forecasting using a clustering approach

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National Proceedings Power and Energy Conference (PECon)

作者： Kh. Sokhanvar A. Karimpour N. Pariz Ferdowsi University of Mashhad Mashhad Iran

This paper presents a new method to forecast the short term electricity price as a kind of time series. A clustering based forecasting method is introduced. The proposed method contains input-output decomposition and using a simple clustering approach to classify them and then for a new input (a specified number of past time series values), these clusters are sorted according to the probabilities calculated by using the Bayespsila formula. The prediction is then generated using the weighted average of the forecasted outputs of M clusters with highest probabilities.

关键词： Clustering algorithms Load forecasting Probability Economic forecasting partitioning algorithms Virtual colonoscopy Environmental factors Industrial control Finance Artificial neural networks

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Waveform relaxation algorithm based on virtual state formulation and its numerical stability

Waveform relaxation algorithm based on virtual state formula...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： H. Asai S. Isobe Dept. of Opt-Electron. & Mech. Eng. Shizuoka Univ. Hamamatsu Japan Department of Opt-Electronic & Mechanical Engineering Faculty of Engineering Shizuoka University Hamamatsu Japan

A description is presented of the waveform relaxation (WR) algorithm with the virtual state formulation technique, where adaptive virtual capacitors are interposed for numerical stability. First, the authors present the virtual state relaxation (VSR) method for the stable convergent simulation of nonlinear circuits. The VSR method is applied to the WR algorithm to exploit the multirate behavior. It is shown that the method allows the use of large timestep sizes in numerical integration, and reduces the total simulation time considerably.< >

关键词： Numerical stability Jacobian matrices Iterative algorithms Nonlinear equations Algorithm design and analysis Numerical analysis Iterative methods Capacitors partitioning algorithms Relaxation methods

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Supervised fuzzy clustering for rule extraction

Supervised fuzzy clustering for rule extraction

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： M. Setnes Control Laboratory Delft University of Technnology Delft Netherlands

The paper is concerned with the application of orthogonal transforms and fuzzy clustering to the extraction of fuzzy rules from data. It is proposed to use the orthogonal least squares method to supervise the progress of the fuzzy clustering algorithm and remove clusters of less importance with respect to fitting the data. Clustering takes place in the product space of systems in and outputs, and each cluster corresponds to a fuzzy IF-THEN rule. By initializing the clustering with an overestimated number of clusters, and subsequently remove less important clusters (rules) as the clustering progresses, it is sought to obtain a suitable partition of the data in an automated. The approach is studied for the fuzzy c-means algorithm and applied to a function approximation example known from the literature.

关键词： Fuzzy systems Data mining Clustering algorithms Approximation algorithms Humans Linear regression Laboratories Space technology State-space methods partitioning algorithms

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A Clustering Approach in Developing Prognostic Systems of Cancer Patients

A Clustering Approach in Developing Prognostic Systems of Ca...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Dechang Chen Kai Xing Donald Henson Li Sheng Arnold M. Schwartz Xiuzhen Cheng Division of Epidemiology and Biostatistics Uniformed Services University of Health Sciences Bethesda MD USA Department of Computer Science George Washington University Washington D.C. DC USA The George Washington University Cancer Institute George Washington University Washington D.C. DC USA Department of Mathematics Drexel University Philadelphia PA USA Department of Pathology George Washington University Medical Center Washington D.C. DC USA

Accurate prediction of survival rates of cancer patients is often key to stratify patients for prognosis and treatment. Survival prediction is often accomplished by the TNM system that involves only three factors: tumor extent, lymph node involvement, and metastasis. This prediction from the TNM has been limited, mainly because other potential prognostic factors are not used in the system. Based on availability of large cancer datasets, it is possible to establish powerful prediction systems by using machine learning procedures and statistical methods. In this paper, we present a clustering based approach to develop prognostic systems of cancer patients. Our method starts with grouping combinations that are formed using levels of factors recorded in the data. The dissimilarity measure between combinations is obtained through a sequence of data partitions produced by multiple clusterings. This dissimilarity measure is then used with a hierarchical clustering method in order to find clusters of combinations. Prediction of survival is made simply by using the survival function derived from each cluster. Our approach admits multiple factors and provides a practical and useful tool in outcome prediction of cancer patients. A demonstration of use of the proposed method is given for lung cancer patients.

关键词： Cancer Neoplasms Clustering methods Lungs Clustering algorithms partitioning algorithms Machine learning Computer science Medical treatment Lymph nodes

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