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sensor array and multichannel signal processing workshop

作者： Necati Gulunay CGGVeritas Research and Development Cairo Egypt

Seismic receiver arrays that are used in modern 3D marine surveys can also be used as 2D sensor arrays in the localization of the diffracted noise sources and hence allow attenuation of such noise from the seismic rec... 详细信息

关键词： Noise Receivers Diffraction Three dimensional displays arrays Imaging Earth

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Primary users detect for Multiple-antenna Cognitive Radio based on Blind Source Separation

Primary users detect for Multiple-antenna Cognitive Radio ba...

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2nd International Symposium on Intelligent Information Technology Application

作者： Xu, Gang Lu, Yourong He, Jun Hu, Ning SW Elect & Telecommun Tech Res Inst Chengdu Peoples R China

ISBN: (纸本)9780769535050

In this paper, we suggest blind source separation (BSS) technology for primary users detect, which is very important in cognitive radio (CR). Multiple-antenna system should be a part of CR. Different antenna receives the same CR signal from different path, if only CR is being working. When primary user starts working, different antenna receives mixed signals of CR and primary user from different path;which can satisfy the BSS situation. CR can separate different signals with little collision. At the next time, CR can jump to next carrywave or modulation type.

关键词： Cognitive radio Blind source separation Chromium Wireless communication Computational intelligence Source separation Neural networks signal processing Receiving antennas sensor systems

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Design of Remote Monitoring System for Complex workshop

Design of Remote Monitoring System for Complex Workshop

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2nd International Symposium on Test Automation and Instrumentation

作者： Wu Xinyi Xue Wendong Huang Wensen Hong Yongqiang Xiamen Univ Dept Mech & Elect Engn Xiamen 361005 Fujian Peoples R China

ISBN: (纸本)9787506292207

Taking the complementary advantages of the analogue video processing technology, ZigBee wireless communication technology and embedded Web server for information collection and transmission, the workshop remote monitoring system is designed, to realize a large-scale, low-power, high-efficiency multi-signal remote supervision. The system hardware platform mainly consists of Video QUAD/MUX Controller TW2834, MPEG Encoder Go7007, 16/32-bit RISC microprocessor S3C2440, ieee 802.15.4 RF chips and other units. Combining with Linux OS, ZigBee Protocol Stack, BOA Webserver and Flash Server Red5, the system realizes the functions of multi-channel analogue video process and shows, ZigBee star topology wireless sensor network and Browser/Server remote information interaction.

关键词： ZigBee red5 wireless sensor networks browser/server

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Canonical decomposition of even higher order cumulant arrays for blind underdetermined mixture identification

Canonical decomposition of even higher order cumulant arrays...

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sensor array and multichannel signal processing workshop

作者： Ahmad Karfoul Laurent Albera Lieven De Lathauwer INSERM U642 Rennes France Leuven Subfaculty Science and Technology Katholieke Universiteit Leuven Kortrijk Belgium

A new family of methods, named 2q-ORBIT (q > 1), is proposed in this paper in order to blindly identify potentially underdetermined mixtures of statistically independent sources. These methods are based on the canonical decomposition of q-th order (q ges 2) cumulants. The latter decomposition is brought back to the decomposition of a third order array whose one loading matrix is unitary. Such a decomposition is then computed by alterning and repeating two schemes until convergence: the first one consists in solving a Procrustes problem while the second one needs to compute the best rank-1 approximation of several q-th order arrays. Computer results show a good efficiency of the proposed methods with respect to classical cumulant-based algorithms especially in the underdetermined case.

关键词： Matrix decomposition sensors signal to noise ratio sensor arrays signal processing algorithms Equations Convergence

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Localization in sensor networks - A matrix regression approach

Localization in sensor networks - A matrix regression approa...

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sensor array and multichannel signal processing workshop

作者： Paul Honeine Cedric Richard Mehdi Essoloh Hichem Snoussi Institut Charles Delaunay (FRE CNRS 2848)-LM2S Université de technologie de Troyes Troyes France

In this paper, we propose a new approach to sensor localization problems, based on recent developments in machine leaning. The main idea behind it is to consider a matrix regression method between the ranging matrix and the matrix of inner products between positions of sensors, in order to complete the latter. Once we have learnt this regression from information between sensors of known positions (beacons), we apply it to sensors of unknown positions. Retrieving the estimated positions of the latter can be done by solving a linear system. We propose a distributed algorithm, where each sensor positions itself with information available from its nearby beacons. The proposed method is validated by experimentations.

关键词： Distance measurement Kernel Optimization Distributed algorithms Wireless sensor networks Network topology Topology

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A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITIONS

A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITION...

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2008 ieee sensor array and multichannel signal processing workshop

作者： Florian Roemer Martin Haardt Communications Research Laboratory Ilmenau University of Technology Ilmenau Germany

In this paper we study the R-way Parallel Factor Analysis (also referred to as R-way PARAFAC) problem. This branch of multi-way signal processing has received increased attention recently which is due to the versatility of the model as well as the identifiability results demonstrating its superiority to matrix-only (2-way) approaches. In R-way PARAFAC analysis, the goal is to decompose an R-dimensional tensor into a minimal sum of rank-1 terms. So far, there exist sub-optimal closed-form solutions as well as iterative techniques for finding these decompositions. However, the latter often require many iterations to converge. In this contribution we demonstrate that the R-way PARAFAC decomposition can be reduced to a set of simultaneous matrix diagonalization problems. Exploiting the structure of the R-dimensional problem, we obtain several estimates for each of the factors and present a "best matching" scheme to select the best estimate for each factor. By means of computer simulations we compare our closed-form solution to an iterative technique and demonstrate the enhanced robustness in critical scenarios.

关键词： Multidimensional signal processing Parameter estimation array signal processing

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Study of signal of roll eccentricity based on wavelet thresholding de-noising

Study of signal of roll eccentricity based on wavelet thresh...

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ieee International workshop on Anti-counterfeiting, Security, Identification, ASID

作者： Jian-rui Zhang Institute of Intelligent Information Processing Guizhou Normal University China

With the ever-increasing demand for the quality of steel plate and strip products, roll eccentricity has become an important factor affecting the product quality. In this paper, the roll eccentricity signal is modeled based on modern signal processing theory. As the data gained from the sensor contain interference, the wavelet threshold de-noising method is developed. By using wavelet analysis, the step in the signal can also be detected. The signal preprocessing is realized. The simulation results to find the optimal threshold of quantitative methods and the most suitable wavelet, to achieve a high-quality signal de-noising. The method has been applied to the scene in the actual production, far superior than the traditional method of noise filter, rolling greatly enhance the accuracy.

关键词： Noise reduction signal processing Steel Strips Interference Wavelet analysis signal analysis signal detection signal denoising Layout

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Auto-zeroed high speed comparator for the column level readout circuit of a CMOS active pixel sensor based detector

Auto-zeroed high speed comparator for the column level reado...

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ieee International workshop on Anti-counterfeiting, Security, Identification, ASID

作者： Yan Li Zhen Ji Yavuz Degerli Texas Instruments DSPs Laboratory Faculty of Information Engineering Shenzhen University Shenzhen China CEA Saclay IRFU/SEDI Gif-sur-Yvette France

The detection systems of future high-energy physics experiments need high resolution pixel detectors allowing auto data sparsification. One solution is the CMOS active pixel sensor based detector, which allows integration of chip-level full data processing circuits. Designed for pixel signal readout, a column-level high speed, low-power and fully offset compensated comparator is developed. For an operation frequency of 100 MHz, the resolution is better than 0.5 mV and the residual offset is only 0.15 mVrms. The power dissipation is about 220 muW. The dimension is 25 mum times 300 mum.

关键词： Circuits Latches Detectors Voltage Physics signal resolution CMOS process Data processing signal design Power dissipation

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multichannel thresholding with sensing dictionaries

Multichannel thresholding with sensing dictionaries

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2nd ieee International workshop on Computational Advances in Multi-sensor Adaptive processing

作者： Gribonval, Remi Mailhe, Boris Rauhut, Holger Schnass, Karin Vandergheynst, Pierre Ecole Polytech Fed Lausanne Signal Proc Inst ITS CH-1015 Lausanne Switzerland

ISBN: (纸本)9781424417131

This paper shows introduces the use sensing dictionaries for p-thresholding, an algorithm to compute simultaneous sparse approximations of multichannel signals over redundant dictionaries. We do both a worst case and average case recovery analyses of this algorithm and show that the latter results in much weaker conditions on the dictionary, sensing dictionary pair. We then do numerical simulations to confirm our theoretical findings, showing that p-thresholding is an interesting low complexity alternative to simultaneous greedy or convex relaxation algorithms for processing sparse multichannel signals with balanced coefficients, and finally point a connection to compressed sensing exploiting the additional freedom in designing the sensing dictionary.

关键词： Multidimensional signal processing

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Parametric GLRT for multichannel adaptive signal detection

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ieee TRANSACTIONS ON signal processing 2007年第11期55卷 5351-5360页

作者： Sohn, Kwang June Li, Hongbin Himed, Braham Stevens Inst Technol Dept Elect & Comp Engn Hoboken NJ 07030 USA USAF Res Lab SNRT Rome NY 13441 USA

This paper considers the problem of detecting a multichannel signal in the presence of spatially and temporally colored disturbance. A parametric generalized likelihood ratio test (GLRT) is developed by modeling the disturbance as a multichannel autoregressive (AR) process. Maximum likelihood (ML) parameter estimation underlying the parametric GLRT is examined. It is shown that the ML estimator for the alternative hypothesis is nonlinear and there exists no closed-form expression. To address this issue, an asymptotic ML (AML) estimator is presented, which yields asymptotically optimum parameter estimates at reduced complexity. The performance of the parametric GLRT is studied by considering challenging cases with limited or no training signals for parameter estimation. Such cases (especially when training is unavailable) are of great interest in detecting signals in heterogeneous, fast changing, or dense-target environments, but generally cannot be handled by most existing multichannel detectors which rely more heavily on training at an adequate level. Compared with the recently introduced parametric adaptive matched filter (PAMF) and parametric Rao detectors, the parametric GLRT achieves higher data efficiency, offering improved detection performance in general.

关键词： generalized likelihood ratio test (GLRT) maximum likelihood (ML) parameter estimation multichannel signal detection parametric models space-time adaptive processing (STAP)

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