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检索条件"主题词=distributed signal processing"

共 131 条记录，以下是71-80 订阅

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A SEMI-CLOSED FORM SOLUTION TO THE SNR BALANCING PROBLEM OF TWO-WAY RELAY NETWORK BEAMFORMING

A SEMI-CLOSED FORM SOLUTION TO THE SNR BALANCING PROBLEM OF ...

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

In this paper, we present a semi-closed form solution to the SNR balancing problem, first considered in [1], in the context of network beamforming design for two-way relay networks. This solution relies on a simple bisection method to obtain the transmit power of one of the two transceivers. Given this transmit power, the relay beamforming weight vector is shown to have a closed-form solution. Simulation results show that the proposed solution has significantly lower computational complexity. We also present a suboptimal solution which does not use the aforementioned bisection algorithm while performs very closely to the optimal beamformer.

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

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An empirical study of collaborative acoustic source localization

An empirical study of collaborative acoustic source localiza...

引用

6th International Symposium on Information processing Sensor Networks

作者： Ali, Andreas M. Yao, Kung Collier, Travis C. Taylor, Charles E. Blumstein, Daniel T. Girod, Lewis Univ Calif Los Angeles Los Angeles CA 90024 USA

ISBN: (纸本)9781595936387

Field biologists use animal sounds to discover the presence of individuals and to study their behavior. Collecting bioacoustic data has traditionally been a difficult and time-consuming process in which researchers use portable microphones to record sounds while taking notes of their own detailed observations. The recent development of new deployable acoustic sensor platforms presents opportunities to develop automated tools for bio-acoustic field research. In this work, we implement an AML-based source localization algorithm, and use it to localize marmot alarm-calls. We assess the performance of these techniques based on results from two field experiments: (1) a controlled test of direction-of-arrival (DOA) accuracy using a pre-recorded source signal, and (2) an experiment to detect and localize actual animals in their habitat, with a comparison to ground truth gathered from human observations. Although small arrays yield ambiguities from spatial aliasing of high frequency signals, we show that these ambiguities are readily eliminated by proper bearing crossings of the DOAs from several arrays. These results show that the AML source localization algorithm can be used to localize actual animals in their natural habitat, using a platform that is practical to deploy.

关键词： bioacoustics distributed signal processing acoustic source localization wireless sensor networks AML

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Embedded Sensor Systems for Health - Providing the Tools in Future Healthcare

Embedded Sensor Systems for Health - Providing the Tools in ...

引用

11th International Conference on Wearable Micro and Nano Technologies for Personalized Health (pHealth)

作者： Linden, Maria Bjorkman, Mats Malardalen Univ Sch Innovat Design & Engn Vasteras Sweden

ISBN: (纸本)9781614993933;9781614993926

Wearable, embedded sensor systems for health applications are foreseen to be enablers in the future healthcare. They will provide ubiquitous monitoring of multiple parameters without restricting the person to stay at home or in the hospital. By following trend changes in the health status, early deteriorations will be detected and treatment can start earlier. Also health prevention will be supported. Such future healthcare requires technology development, including miniaturized sensors, smart textiles and wireless communication. The tremendous amount of data generated by these systems calls for both signal processing and decision support to guarantee the quality of data and avoid overflow of information. Safe and secure communications have to protect the integrity of the persons monitored.

关键词： Wearable sensors wireless body area network safe communication distributed signal processing decision support

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BAYESIAN QUADRATIC NETWORK GAME FILTERS

BAYESIAN QUADRATIC NETWORK GAME FILTERS

引用

IEEE International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Eksin, Ceyhun Molavi, Pooya Ribeiro, Alejandro Jadbabaie, Ali Univ Penn Dept Elect & Syst Engn Philadelphia PA 19104 USA

ISBN: (纸本)9781479903566

A repeated network game where agents' utilities depend on information and payoff externalities is considered. Agents play Bayesian Nash Equilibrium strategies with respect to their beliefs on the state of the world and the actions of all other nodes in the network. These beliefs are refined over subsequent stages based on the observed actions of neighboring peers. This paper introduces the Quadratic Network Game (QNG) filter that agents can run locally to update their beliefs, select corresponding optimal actions, and eventually learn a sufficient statistic of the network's state. The QNG filter is demonstrated on a coordination game.

关键词： Network Games Bayesian Nash Equilibrium Linear Filtering distributed signal processing

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Robust distributed Block LMS over WSN in Impulsive Noise

Robust Distributed Block LMS over WSN in Impulsive Noise

引用

8th International Conference on distributed Computing and Internet Technologies (ICDCIT 2012)

作者： Panigrahi, Trilochan Panda, Ganapati Mulgrew, B. Natl Inst Technol Rourkela Dept ECE Rourkela 769008 India Indian Inst Technol Bhubaneswar Sch Elect Sci Bhubaneswar Orissa India Univ Edinburgh IDCOM Edinburgh Midlothian Scotland

ISBN: (纸本)9783642280726;9783642280733

In wireless sensor network each sensor node collects data related to some unknown parameters, corrupted by independent Gaussian noise. Then the objective is to estimate the parameter from the data collected across the network in distributed manner. The distributed estimation algorithm should be energy efficient, provides high estimation accuracy, and is fast in convergence. But the conventional distributed algorithm involves significant communication overhead and is also not robust to the impulsive noise which is common in wireless sensor network environment. Consequently these algorithms defeat the basic purpose of wireless sensor network. This paper studies the problem of robust adaptive estimation in impulsive noise environment using robust cost function like Wilcoxon norm and Huber cost function. Further in order to reduce the amount of communication overhead, block distributed LMS is incorporated.

关键词： Wireless sensor network contaminated Gaussian noise distributed signal processing incremental LMS Wilcoxon norm

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distributed ESTIMATION OF CROSS-CORRELATION FUNCTIONS IN AD-HOC MICROPHONE ARRAYS 23

DISTRIBUTED ESTIMATION OF CROSS-CORRELATION FUNCTIONS IN AD-...

引用

23rd European signal processing Conference (EUSIPCO)

作者： van Waterschoot, Toon Katholieke Univ Leuven Dept Elect Engn ESAT STADIUS ETC Kasteelpk Arenberg 10 B-3001 Leuven Belgium

ISBN: (纸本)9780992862633

In this paper, we address the problem of estimating the cross-correlation function between two microphone signals recorded in different nodes of an ad-hoc microphone array or wireless acoustic sensor network, where the transmission of the entire microphone signal from one node to another is undesirable due to power and/or bandwidth constraints. We show that instead of directly computing the cross-correlation function, it can be estimated as the solution to a deconvolution problem. This deconvolution problem can be separated into two subproblems, each of which depends on one microphone signal and an auxiliary signal derived from the other microphone signal. Three different strategies for solving this deconvolution problem are proposed, in which the two subproblems are solved jointly (symmetric deconvolution), separately (asymmetric deconvolution) or in a consensus framework (consensus deconvolution). Simulation results illustrate the performance difference in terms of estimation accuracy, noise robustness, and transmission requirements.

关键词： distributed signal processing distributed optimization cross-correlation function ad-hoc microphone array wireless acoustic sensor network

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distributed Detection and Imaging in MIMO Radar Network Based on Averaging Consensus 10

Distributed Detection and Imaging in MIMO Radar Network Base...

引用

10th IEEE Sensor Array and Multichannel signal processing Workshop (SAM)

作者： Zabolotsky, Anton A. Mavrychev, Evgeny A. Nizhnii Novgorod State Tech Univ Dept Informat Radio Syst 24 Minin St Nizhnii Novgorod Russia

ISBN: (纸本)9781538647523

In this paper, we consider distributed signal processing in a MIMO radar network. We suppose that transmitting and receiving nodes of MIMO radar are distributed in a large-scale area. In this network the neighboring receiving nodes communicate with each other to exchange data. A fully distributed algorithm for detection and imaging is proposed. This algorithm is based on the averaging consensus approach. The effectiveness of the proposed technique is confirmed by numerical examples. It is compared to the centralized solution in a fusion center, the local solution in an individual receiving node and the proposed distributed algorithm.

关键词： MIMO radar network distributed signal processing averaging consensus algorithm

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Progressive distributed Estimation over Noisy Channels in Wireless Sensor Networks

Progressive Distributed Estimation over Noisy Channels in Wi...

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IEEE International Conference on Acoustics, Speech and signal processing

作者： Zhang, Li Zhang, Xian-Da Ho, Tracey Dikaliotis, Theodoros Tsinghua Univ Dept Automat Beijing 100084 Peoples R China CALTECH Dept Elect Engn Pasadena CA 91125 USA

ISBN: (纸本)9781424423538

This paper presents a new progressive distributed estimation scheme (DES) along with the power scheduling among sensors under AWGN channels. The progressive DES consists of a transmission bit allocation scheme and a quasi best linear unbiased estimate (BLUE) of the unknown parameter at each sensor. This scheme is shown to outperform the traditional progressive DES. Moreover, the power scheduling among sensors, which minimizes the total transmission power subject to the desired MSE performance tolerance, is formulated as a convex problem and the optimal solution is derived analytically.

关键词： distributed estimation incremental quantization distributed signal processing sensor networks

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DECENTRALIZED INDEPENDENT VECTOR ANALYSIS

DECENTRALIZED INDEPENDENT VECTOR ANALYSIS

引用

IEEE International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Wojtalewicz, Nikolas P. Silva, Rogers F. Calhoun, Vince D. Sarwate, Anand D. Plis, Sergey M. New Coll Florida Sarasota FL 34243 USA Mind Res Network Albuquerque NM USA Rutgers State Univ New Brunswick NJ USA

ISBN: (纸本)9781509041176

Independent vector analysis (IVA) is an approach for joint blind source separation of several data sets that learns simultaneous unmixing transforms for each set. It assumes corresponding sources from different data sets to be statistically dependent. One of the main advantages is IVA's ability to retain subject-specific differences while simplifying comparison across subjects as the resulting components have the same order. The latter is an instrumental property for enabling collaboration between remote sites without sharing their data, which may be required because of ethical, privacy or efficiency concerns. This paper proposes a new decentralized algorithm for IVA that exploits the structure of the objective function. A centralized aggregator coordinates IVA algorithms at multiple sites using message passing, parallelizing the computation and limiting the amount of communication. Thus, the algorithm enables a plausibly private collaboration across multiple sites. Besides enabling analysis of decentralized data, our approach improves the running time of IVA when used locally.

关键词： IVA distributed signal processing blind source separation decentralized data

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Convergence Rates for Cooperation in Heterogeneous Populations

Convergence Rates for Cooperation in Heterogeneous Populatio...

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46th Asilomar Conference on signals, Systems and Computers

作者： Bean, Andrew Kairouz, Peter Singer, Andrew Univ Illinois Urbana IL 61801 USA

ISBN: (纸本)9781467350518

We consider the problem of cooperative distributed estimation within a network of heterogeneous agents. In particular, we study the situation where each agent observes an independent stream of Bernoulli random variables, and the goal is for each to determine its own Bernoulli parameter. The agents of this population can be categorized into a small number of subgroups, where within each group the agents all have identical Bernoulli parameters. For a distributed algorithm based on consensus strategies, we examine the rate at which the agent's estimates converge to the correct values. We show that the expected squared error decreases nearly as fast as centralized ML estimation in a homogeneous population. In a heterogeneous population, we derive an approximation to the expected squared error, as a function of the number of observations. Finally, we present simulation results that compare the predicted expected squared error to that observed in the simulations.

关键词： gossip algorithms consensus diffusion adaptation distributed estimation distributed signal processing

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