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检索条件"主题词=distributed signal processing"

共 131 条记录，以下是81-90 订阅

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distributed CROSS-RELATION-BASED FREQUENCY-DOMAIN BLIND SYSTEM IDENTIFICATION USING ONLINE-ADMM 17

DISTRIBUTED CROSS-RELATION-BASED FREQUENCY-DOMAIN BLIND SYST...

引用

17th International Workshop on Acoustic signal Enhancement (IWAENC)

作者： Blochberger, M. Elvander, F. Ali, R. Moonen, M. van Waterschoot, T. Ostergaard, J. Jensen, J. Katholieke Univ Leuven Dept Elect Engn ESAT STADIUS B-3001 Leuven Belgium Aalborg Univ Dept Elect Syst DK-9220 Aalborg Denmark

ISBN: (数字)9781665468671

ISBN: (纸本)9781665468671

In this paper, we propose a distributed cross-relation-based adaptive algorithm for blind identification of single-input multiple-output (SIMO) systems in the frequency domain, using the alternating direction method of multipliers (ADMM) in a wireless sensor network (WSN). The network consists of a fixed number of nodes each equipped with a processing unit and a sensor that represents an output channel of the SIMO system. The proposed algorithm exploits the separability of the cross-channel relations by splitting the multichannel identification problem into sub-problems containing a subset of channels, in a way that is determined by the network topology. Each node delivers estimates for the subset of channel frequency responses, which are then combined into a consensus estimate per channel using general-form consensus ADMM in an adaptive updating scheme. Using numerical simulations, we show that it is possible to achieve convergence speeds and steady-state misalignment values comparable to fully centralized low-cost frequency-domain algorithms.

关键词： blind system identification multichannel signal processing distributed signal processing admm online-admm

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Bandwidth-efficient distributed estimation in inhomogeneous wireless sensor networks

Bandwidth-efficient distributed estimation in inhomogeneous ...

引用

IEEE Wireless Communications and Networking Conference

作者： Zhang, Li Zhang, Xian-Da Gao, Qiubin Han, Fang-Ming Tsinghua Univ Dept Automat Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781424419968

This paper presents a distributed estimation scheme (DES) along with the bit allocation algorithm, which minimizes the total required bandwidth while ensuing a given average estimation mean-squared error (MSE). The DES comprises of a probabilistic Lloyd-Max quantization rule, and a best linear unbiased estimation (BLUE). Since the optimum bit allocation problem does not have a closed form, we present a suboptimal solution utilizing the alternating minimization (AM) algorithm. Finally, simulation results are provided to show the effectiveness of the proposed DES along with the bit allocation algorithm.

关键词： distributed estimation quantization distributed signal processing sensor networks

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On spatial gossip algorithms for average consensus

On spatial gossip algorithms for average consensus

引用

14th IEEE/SP Workshop on Statistical signal processing

作者： Rabbat, Michael G. McGill Univ Dept Elect & Comp Engn Montreal PQ Canada

ISBN: (纸本)9781424411979

This paper investigates the use of spatial gossip to compute the average consensus in networks such as grids or random geometric graphs, where connectivity is a function of proximity. Randomized gossip is a framework for distributed computation where, at each iteration, a random pair of nodes exchanges information, and then updates their local values by averaging. This simple protocol converges to an average consensus: every node obtains the average of the initial values across the network. In spatial gossip, if the distance between two nodes is d, then they communicate with probability proportional to d(-beta) for some beta >= 0. The special case beta = 0 corresponds to an algorithm known in the sensor network literature as geographic gossip. Dimakis et al have shown that geographic gossip computes the average to accuracy n(-1) in O(n(3/2)V root log n) transmissions. In this paper we show that the same rates are achieved for beta = 2 and beta = 3. Each setting offers a different balance between the rate of convergence (in gossip rounds) and the average number of transmissions per gossip round. We illustrate, via simulation, that spatial gossip with beta = 2 generally yields superior performance over geographic gossip by a constant factor.

关键词： sensor networks aggregation gossip algorithms average consensus distributed signal processing

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distributed network of underwater sensors based on local time-frequency coherence analysis

Distributed network of underwater sensors based on local tim...

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MTS/IEEE Oceans Conference

作者： Dadouchi, Florian Ioana, Cornel Gervaise, Cedric Mars, Jerome I. Mallet, Julien Philippe, Olivier Mauuary, Didier Jespers, Stephane Grenoble Inst Technol GIPSA Lab St Martin Dheres France OSEANSAS Toulon France CYBERIO Meylan France DGA Direct Tech Bagneux France

ISBN: (纸本)9780933957404

Underwater acoustic sensor networks are an important element in a large number of applications such as surveillance, environment monitoring. The development of an autonomous sensor system imposes the distribution of the data processing at the level of sensors. This operation is subject to a trade-off between the processing efficiency and the algorithmic complexity that influences the power consumption. In the case of current networks, a common way to answer to this trade-off issue is to process data (detection, recording, transmission.) when the energy of the observed signal, in an arbitrary analysis window, exceeds a given threshold. In this paper, we propose an underwater network configuration that is composed of sensors implementing a different processing approach, based on the hypothesis of a local time-frequency coherence (FM sweep). The results obtained on real data illustrate the efficiency of this algorithm, in terms of signal's characterization and lower communication bit rates.

关键词： distributed signal processing underwater source localization time-frequency analysis

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Diffusion Least-Mean Squares over distributed Networks in the Presence of MAC Errors

Diffusion Least-Mean Squares over Distributed Networks in th...

引用

46th Asilomar Conference on signals, Systems and Computers

作者： Ghazanfari-Rad, Saeed Labeau, Fabrice McGill Univ Dept Elect & Comp Engn Montreal PQ H3A 0E9 Canada

ISBN: (纸本)9781467350518

This paper presents the formulation and steady-state analysis of the distributed estimation algorithms based on diffusion cooperation scheme, in which all nodes in the network communicate employing a non-ideal channel access mechanism. We formulate and study a two-node network and derive the closed-form expressions of the steady-state mean-square deviation (MSD). We also assess the mean performance and stability condition. The proposed analytical framework enables us to investigate the effects of the medium access control (MAC) layer performance on the behavior of the diffusion least-mean squares (LMS) algorithm in terms of the convergence speed and the steady-state error that is validated by performing Monte Carlo simulations. Simulation and analysis confirm that a high probability of collision at the MAC level, results in lower convergence speed and higher steady-state MSD for distributed estimation algorithm.

关键词： Adaptive networks diffusion LMS algorithm MAC layer distributed estimation distributed signal processing

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ADMM Based distributed Volterra Modeling of Nonlinear Dynamical Systems Using Ad-Hoc WSNs 9

ADMM Based Distributed Volterra Modeling of Nonlinear Dynami...

引用

9th International Conference on Computing, Communication and Networking Technologies (ICCCNT)

作者： Kapgate, Sachin N. Gupta, Saurav Sahoo, Priyanka Priyadarshini Sahoo, Ajit Kumar Natl Inst Technol Dept Elect & Commun Engn Rourkela India

ISBN: (纸本)9781538644300

To model the behavior of nonlinear dynamical systems using wireless sensor networks (WSNs), the development of computation and energy efficient distributed modeling techniques is of crucial importance. In this work, Volterra model is considered for the modeling of nonlinear systems because of its significant modeling capability and generalized nonlinear structure. For real-time estimation of the Volterra model parameters, a simple distributed algorithm is designed for a particular framework of WSNs having predefined bridge sensor nodes. The pertinent cost function is expressed as an unconstrained minimization problem using a decomposable augmented Lagrangian form. To facilitate the distributed convex optimization, the augmented Lagrangian form is minimized using alternating direction method of multipliers. The communication and computational complexities involved in the proposed methodology are provided to show its effectiveness in the real-time applications over centralized and non-cooperative solutions. The convergence analysis is provided to guarantee the mean stability of the proposed algorithm. Simulation results obtained under the noisy environment are plotted to demonstrate the effective performance of the proposed algorithm.

关键词： distributed signal processing nonlinear dynamical Systems Volterra model wireless sensor network Least mean square

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Optimal Combination Weight for Sparse Diffusion Least-Mean-Square based on Consensus Propagation

Optimal Combination Weight for Sparse Diffusion Least-Mean-S...

引用

Asia-Pacific-signal-and-Information-processing-Association Annual Summit and Conference (APSIPA ASC)

作者： Nakai-Kasai, Ayano Hayashi, Kazunori Kyoto Univ Kyoto Japan

ISBN: (纸本)9789881476883

This paper considers distributed adaptive signal processing for tracking an unknown sparse parameter vector in large-scale networks. We propose a sparsity-promoting diffusion least-mean-square algorithm based on consensus propagation, which is an average consensus algorithm using message passing techniques. The main contributions of the paper are optimizing coefficients in the algorithm in terms of the steady-state error to achieve better convergence and robustness, and presenting the adaptive implementation.

关键词： Diffusion LMS distributed signal processing average consensus sparseness

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Network beamforming based on second order statistics of the channel state information

Network beamforming based on second order statistics of the ...

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33rd IEEE International Conference on Acoustics, Speech and signal processing

作者： Havary-Nassab, Veria Shahbazpanahi, Shahram Grami, Ali Luo, Zhi-Quan Univ Western Ontario Fac Engn & Appl Sci Inst Technol Oshawa ON L1H 7K4 Canada

ISBN: (纸本)9781424414833

The problem of distributed beamforming is considered for a network which consists of a transmitter, a receiver, and r relay nodes. Assuming that the second order statistics of the channel coefficients are available, we design a distributed beamforming technique via maximization of the receiver signal-to-noise ratio (SNR) subject to individual relay power constraints. We show that using semi-definite relaxation, this SNR maximization can be turned into a convex feasibility semi-definite programming problem, and therefore, it can be efficiently solved using interior point methods. We also obtain a performance bound for the semi-definite relaxation and show that the semi-definite relaxation approach provides a c-approximation to the (nonconvex) SNR maximization problems where c = O((log r)(-1)) and r is the number of relays.

关键词： distributed beamforming relay networks semidefinite programming convex feasibility problem distributed signal processing

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ACHIEVABLE RATE REGION AND SUM-RATE MAXIMIZATION FOR NETWORK BEAMFORMING FOR BI-DIRECTIONAL RELAY NETWORKS

ACHIEVABLE RATE REGION AND SUM-RATE MAXIMIZATION FOR NETWORK...

引用

2010 IEEE International Conference on Acoustics, Speech, and signal processing

作者： Shahbazpanahi, Shahram Dong, Min Univ Ontario Inst Technol Fac Engn & Appl Sci Oshawa ON L1H 7K4 Canada

ISBN: (纸本)9781424442966

We study the sum-rate maximization approach when applied to design a decentralized beamformer for two-way relay networks. Considering a constraint on the total transmit power consumed in the whole network, we prove that sum-rate maximization is equivalent to an SNR balancing approach where the smallest of the two receive SNRs is maximized subject to the same total power constraint.

关键词： distributed beamforming ad hoc relay networks two-way relaying distributed signal processing SNR balancing optimal power allocation bi-directional relaying

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ASYNCHRONOUS distributed EDGE-VARIANT GRAPH FILTERS

ASYNCHRONOUS DISTRIBUTED EDGE-VARIANT GRAPH FILTERS

引用

IEEE Data Science Workshop (DSW)

作者： Coutino, Mario Leus, Geert Delft Univ Technol Delft Netherlands

ISBN: (纸本)9781728107080

As the size of the sensor network grows, synchronization starts to become the main bottleneck for distributed computing. As a result, efforts in several areas have been focused on the convergence analysis of asynchronous computational methods. In this work, we aim to cross-pollinate distributed graph filters with results in parallel computing to provide guarantees for asynchronous graph filtering. To alleviate the possible reduction of convergence speed due to asynchronous updates, we also show how a slight modification to the graph filter recursion, through operator splitting, can be performed to obtain faster convergence. Finally, through numerical experiments the performance of the discussed methods is illustrated.

关键词： asynchronous filtering distributed signal processing edge-variant graph filters graph filters graph signal processing

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