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European signal processing conference

作者： Hyunggon Park Nikolaos thomos Pascal Frossard Multimedia Communications and Networking Laboratory Ewha Womans University Signal Processing Laboratory (LTS4) Ecole Polytechnique Federale de Lausanne (EPFL)

this paper addresses the problem of the distributed delivery of correlated data sources with help of network coding. Network coding provides an alternative to routing algorithms and offers improved system performance, robustness and throughput, with no need of deploying sophisticated routing strategies. However, the performance is directly driven by the number of innovative data packets that reach the receiver. If the number of received innovative data packets is significantly small, the decoder cannot perfectly recover the trans- mitted information. However, we show that the correlation between the data sources can be used at decoder for effective approximate decoding. We analytically investigate the impact of the network coding algorithm, and in particular, of the size of finite fields on the decoding performance. then, we determine an optimal field size that minimizes the expected decoding error, which represents a trade-off between quantization of the source data and probability of decoding error. the network coding with approximate decoding algorithm is implemented in illustrative multimedia streaming and sensor network applications. In both cases, the experimental results confirm the field size analysis and illustrate the effectiveness of approximate decoding of correlated data.

关键词： Decoding Encoding Network coding Correlation Approximation methods Distributed databases signal processing

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MULTICHANNEL COMPRESSED SENSING VIA SOURCE SEPARATION FOR HYPERSPECTRAL IMAGES

MULTICHANNEL COMPRESSED SENSING VIA SOURCE SEPARATION FOR HY...

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European signal processing conference

作者： Mohammad Golbabaee Simon Arberet Pierre Vandergheynst Signal Processing Institute Ecole Polytechnique Federale de Lausanne (EPFL)

this paper describes a novel framework for compressive sampling of multichannel signals that are highly correlated across the channels. In this work, we assume few number of independent sources are generating the multichannel observations based on a linear mixture model. Moreover, sources are assumed to have sparse/compressible representations in some orthonormal basis. the main contribution of this paper lies in rephrasing the compressed sampling of multichannel data as the compressive source separation problem by knowing the mixture parameters. A number of simulations measure the performance of our recovery algorithm. Comparing to the classical CS scheme -which recovers data of all channels separately- ours indicates a significant reduction in both, the number of measurements to be sent and the complexity of the decoding algorithm (i.e., scaling by the number of sources rather than the number of channels). We demonstrate an application of our scheme in acquisition of the Hyperspectral images. Our algorithm proposes an accurate, low cost and fast recovery from small number of the transmitted measurements that are taken by a low resolution camera.

关键词： Compressed sensing Hyperspectral images Mixture model Source separation Sparsity L_1-minimization

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Multi-radar system database integration using metrized small world technology

Multi-radar system database integration using metrized small...

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International conference on Microwaves, Radar and Wireless Communications

作者： Dmitry Ponomarev Vladimir Krylov Yuri Pankratov Mera Laboratories Nizhny Novgorod Russia

the present article describes the possibility of integrating the data from several radars with shared radiolocation areas in order to acquire precise information about the targets by means of analyzing the events in neighboring spatiotemporal resolution elements. the paper suggests an algorithm for integrating the data based on creating the graph which possesses the characteristics of the “Metrized small World”. A possibility of processing the integrated data in real time is analyzed. the article describes efficient metrics for integrating multi-radar data into a single Metrized small World graph. Examples of such algorithms are given.

关键词： Spatial databases Spatial resolution Bandwidth Costs data analysis Distributed databases Radar scattering signal resolution Information analysis Spatiotemporal phenomena

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Network Coding aware Rate Selection in multi-rate IEEE 802.11

Network Coding aware Rate Selection in multi-rate IEEE 802.1...

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International conference on Network Protocols

作者： Raju Kumar Srikar Tati Felipe de Mello Srikanth V. Krishnamurthy thomas La Porta Computer Science and Engineering Pennsylvania State University University Park PA USA Computer Science University of Massachusetts Amherst MA USA Computer Science and Engineering University of California Riverside CA USA

Network coding has been proposed as an alternative to the conventional store-and-forward routing paradigm for data delivery in networks. When deployed in a multi-rate wireless network, network coding has to interact with rate adaptation. When multicasting packets (a requirement of network coding) in a multi-rate IEEE 802.11 wireless network, one must use care when selecting the transmission rate to use. We refer to this problem as rate selection. We analyze the performance of network coding for a small set of scenarios representative of common topologies in a network that lead to coding opportunities. Based on this analysis, we present our Network Coding aware Rate Selection (NCRS) algorithm which takes into account transmission rates used for unicast links to all multicast targets. Simulation results show that in a multi-hop wireless network, network coding with NCRS achieves up to 24% more gain over routing than network coding with other rate selection algorithms.

关键词： Network coding signal to noise ratio throughput Encoding Routing Wireless networks IEEE 802.11g Standard

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Passive interference measurement in Wireless Sensor Networks

Passive interference measurement in Wireless Sensor Networks

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International conference on Network Protocols

作者： Shucheng Liu Guoliang Xing Hongwei Zhang Jianping Wang Jun Huang Mo Sha Liusheng Huang USTC-City Joint Advanced Research Centre University of Science and Technology China City University of Hong Kong Hong Kong China Michigan State University USA Wayne State University USA Washington University of Saint Louis USA

Interference modeling is crucial for the performance of numerous WSN protocols such as congestion control, link/channel scheduling, and reliable routing. In particular, understanding and mitigating interference becomes increasingly important for Wireless Sensor Networks (WSNs) as they are being deployed for many data-intensive applications such as structural health monitoring. However, previous works have widely adopted simplistic interference models that fail to capture the wireless realities such as probabilistic packet reception performance. Recent studies suggested that the physical interference model (i.e., PRR-SINR model) is significantly more accurate than existing interference models. However, existing approaches to physical interference modeling exclusively rely on the use of active measurement packets, which imposes prohibitively high overhead to bandwidth-limited WSNs. In this paper, we propose the passive interference measurement (PIM) approach to tackle the complexity of accurate physical interference characterization. PIM exploits the spatiotemporal diversity of data traffic for radio performance profiling and only needs to gather a small amount of statistics about the network. We evaluate the efficiency of PIM through extensive experiments on both a 13-node and a 40-node testbeds of TelosB motes. Our results show that PIM can achieve high accuracy of PRR-SINR modeling with significantly lower overhead compared with the active measurement approach.

关键词： Interference signal to noise ratio Wireless sensor networks Computational modeling Particle measurements Atmospheric measurements Wireless communication

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Detection and Localization of Multiple Unresolved Extended targets via Monopulse Radar signal processing

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2009年第2期45卷 455-472页

作者： Zhang, Xin Willett, Peter Bar-Shalom, Yaakov United Technol Res Ctr E Hartford CT 06108 USA Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

When the size of targets is comparable to the range resolution of monopulse radars, these targets should be considered as extended rather than point targets. If several closely-spaced targets fall within the same radar beam and between adjacent matched filter samples in range, the full monopulse information from all of these samples can and should be used to resolve these targets, i.e., estimate the number of targets and their respective angles-of-arrival and ranges. To detect and localize multiple unresolved extended targets, we establish a model for monopulse radar returns from extended objects, and present a maximum likelihood estimator (MLE) to localize the targets. Rissanen's minimum description length (MDL) criterion will be used to decide the number of existing extended objects. We also derive the upper limit on the number of targets and their scattering centers that can be resolved, and we provide necessary conditions for these targets to be uniquely identified. We compare the new extended target monopulse processing scheme with previously developed point-target monopulse techniques in the simulations.

关键词： RADAR ELECTRONIC pulse techniques ELECTRONIC systems signal processing -- Digital techniques MACHINE theory

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Social search in "small-world" experiments 09

Social search in "small-world" experiments

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18th International World Wide Web conference, WWW 2009

作者： Goel, Sharad Muhamad, Roby Watts, Duncan Yahoo Research 111 West 40th Street New York NY 10018 United States Department of Sociology Columbia University 420 West 118th Street New York NY 10027 United States

ISBN: (纸本)9781605584874

the "algorithmic small-world hypothesis" states that not only are pairs of individuals in a large social network connected by short paths, but that ordinary individuals can find these paths. Although theoretically plausible, empirical evidence for the hypothesis is limited, as most chains in "small-world" experiments fail to complete, thereby biasing estimates of "true" chain lengths. Using data from two recent small-world experiments, comprising a total of 162,328 message chains, and directed at one of 30 "targets" spread across 19 countries, we model heterogeneity in chain attrition rates as a function of individual attributes. We then introduce a rigorous way of estimating true chain lengths that is provably unbiased, and can account for empirically-observed variation in attrition rates. Our findings provide mixed support for the algorithmic hypothesis. On the one hand, it appears that roughly half of all chains can be completed in 6-7 steps-thus supporting the "six degrees of separation" assertion-but on the other hand, estimates of the mean are much longer, suggesting that for at least some of the population, the world is not "small" in the algorithmic sense. We conclude that search distances in social networks are fundamentally different from topological distances, for which the mean and median of the shortest path lengths between nodes tend to be similar. Copyright is held by the International World Wide Web conference Committee (IW3C2).

关键词： Chains

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Optimal sure parameters for sigmoidal wavelet shrinkage

Optimal sure parameters for sigmoidal wavelet shrinkage

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17th European signal processing conference, EUSIPCO 2009

作者： Atto, Abdourrahmane M. Pastor, Dominique Mercier, Gregoire Institut TELECOM TELECOM Bretagne LAB-STICC CNRS UMR 3192 Technopôle Brest-Iroise CS 838 18 29238 Brest Cedex 3 France

this paper provides a SURE optimization for the parameters of a sub-class of smooth sigmoid based shrinkage functions. the optimization is performed on an unbiased estimation risk obtained by using sigmoid shrinkage functions. the SURE sigmoid shrinkage performance measurements are compared to those of the SURELET (SURE linear expansion of thresholds) parameterization. It is shown that the SURE sigmoid shrinkage performs better than the SURELET parameterization on most standard images. the relevance of SigShrink is reinforced by the flexible spatial adaptation it provides thanks to its parameters: a threshold for discriminating large and small data and an attenuation degree to control the shrinkage imposed to data with small amplitudes. © EURASIP, 2009.

关键词： Shrinkage

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Target detection by distributed sensors: distributed sensor concept-DISCO for small target detection

Target detection by distributed sensors: distributed sensor ...

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20th conference on signal and data processing of small targets

作者： Rafailov, Michael K. QinetiQ NA Reston VA 20191 USA

ISBN: (纸本)9780819471604

Distributed Sensor Concept - DISCO was proposed [I] for multiplication of individual sensor capabilities through non-coherent cooperative target engagement. the signal processing technique for DISCO is Recursive Adaptive Frame Integration of Limited data - RAFIL technique [2] that was initially proposed as a way to improve the SNR [3], reduce data rate [4] and mitigate FPA noise for IR sensors [5]. In DISCO, the RAFIL technique is used in a segmented way, when constituencies of the technique are spatially and temporally separated between individual sensors. Each sensor provides to and receives data from other sensors in the network. In this paper efficiency of DISCO is discussed for acquisition, accurate handover and track correlation of small targets.

关键词： multiple sensor system distributed sensors distributed apertures accurate target detection frame integration data rate recursive processing double threshold

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Robust scale invariant small target detection using the Laplacian scale-space theory

Robust scale invariant small target detection using the Lapl...

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20th conference on signal and data processing of small targets

作者： Kim, Sungho Yang, Yukyung Lee, Joohyoung Park, Yongchan Agcy Defense Dev Taejon 305600 South Korea

ISBN: (纸本)9780819471604

this paper presents a new small target detection method using scale invariant feature. Detecting small targets whose sizes are varying is very important to automatic target detection in infrared search and track (IRST). the conventional spatial filtering methods with fixed sized kernel show limited target detection performance for incoming targets. the scale invariant target detection can be defined as searching for maxima in the 3D (x, y, and scale) representation of an image with the Laplacian function. the scale invariant feature can detect different sizes of targets robustly. Experimental results with real FUR images show higher detection rate and lower false alarm rate than conventional methods. Furthermore, the proposed method shows very low false alarms in scan-based IR images than conventional filters.

关键词： small target robust detection varying size scale invariant scale-space

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