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检索条件"主题词=distributed signal processing"

共 131 条记录，以下是101-110 订阅

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distributed Convex Optimization: Based on Monotone Operator Theory

Distributed Convex Optimization: Based on Monotone Operator ...

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作者： Thomas William SHERSON Delft University of Technology

学位级别：博士

FOLLOWING their conception in the mid twentieth century, the world of computers has evolved from a landscape of isolated entities into a sprawling web of interconnected machines. Yet, given this evolution, many of the methods we use for allowing computers to work together still reflect their inherently isolated origins with the aggregation of data or master-slave relationships still commonly seeing use. While sufficient for some types of applications, these approaches do not naturally reflect the collaboration strategies we observe in nature and so the question is raised as to whether we can do better? In parallel to the improvements in computer to computer communication, the emer- gence of new paradigms such as the Internet of Things (IoT), Big Data processing and cloud computing in recent years has placed an increasing importance on networked systems in many facets of the modern world. From power grid management, to au- tonomous vehicle navigation, to even our basic means of interaction through social me- dia, these networks are a pervasive presence in our day to day lives. The vast amounts of data generated by these networks and their ever increasing sizes makes it impractical if not impossible to resort to traditional centralized processing and therefore necessitates the search for new methods of signal processing within networked systems. In this thesis we approach the task of distributed signal processing by exploiting the synergy between such tasks and equivalent convex optimization problems. Specifically, we focus on the task of distributed convex optimization, that of solving optimization problems involving groups of computers in a collaborative manner and the develop- ment of distributed solvers for such tasks. Such solvers distinguish themselves by only allowing local computations at each computer in a network and the exchange of infor- mation between connected computers. In this way, distributed solvers naturally respect the structure of the underlying n

关键词： distributed signal processing Convex Optimization Monotone Operator Theory Wireless Sensor Networks

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A holographic approach to image processing

A holographic approach to image processing

引用

IEEE 15th signal processing and Communications Applications Conference

作者： Demirkol, Askin Woodley, Robert S. Acar, Levent Sakarya Univ Elekt Elekt Muhendisligi Sakarya Turkey Univ Missouri Dept Elect Engn Rolla MO USA

ISBN: (纸本)9781424407194

In this document, A distrubuted image processing based on the mathematics of holographic storage is presented. This work was inspired by the distrubuted principles between wave propagation and subsequent interference patterns seen in holograms. We then analyzed the mathematics to produce a general mathematical description of the holographic process. From a generalized case of this analysis we are able to propose this way for works in some engineering fields such as radar, control and neural networks.

关键词： distributed signal processing image processing holographic image processing holographic restoration

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distributed Data Classification in Underwater Acoustic Sensors based on Local Time-Frequency Coherence Analysis

Distributed Data Classification in Underwater Acoustic Senso...

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Oceans Conference

作者： Petrut, Teodor Ioana, Cornel Mauuary, Didier Mallet, Julien Phillipe, Olivier Grenoble Inst Technol GIPSA Lab St Martin Dheres France CYBERIO Meylan France OSEAN SAS Toulon France

ISBN: (纸本)9781479936465

This paper introduces a stochastic approach that considers the distributed classification problem for a network of underwater acoustic sensors. The proposed classifier applies the third order polynomial regression to the instantaneous frequency extracted from time-frequency representation of different classes of signals and represent the polynomial's coefficients in a three-dimensional representation space. This automatic classifier is then compared to a non-parametric classifier based on the training of a standard neural network. The results of the proposed method on real data illustrate the efficiency of this algorithm, in terms of signal's characterization and lower communication bit rates between each sensor and the data center.

关键词： signal classification neural network clustering pattern recognition distributed signal processing time-frequency analysis

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Acoustic source localization using the acoustic ENSBox

Acoustic source localization using the acoustic ENSBox

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6th International Symposium on Information processing Sensor Networks

作者： Ali, Andreas M. Yao, Kung Collier, Travis C. Taylor, Charles E. Blurnstein, Daniel I. 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. The recent development of new deployable acoustic sensor platforms presents opportunities to develop automated tools for bio-acoustic field research. In this work, we demonstrate a real-time wireless sensor system that implements an AML-based source localization algorithm. We will demonstrate a system that is easy to set up and that can localize a whistle in the demonstration area in real time. This demonstration will use the techniques we described in our corresponding paper [1].

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

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Statistical signal processing in Engineering 1

引用

2017年

作者： Umberto Spagnolini

ISBN: (数字)9781119294016

ISBN: (纸本)9781119293972

A problem-solving approach to statistical signal processing for practicing engineers, technicians, and graduate students This book takes a pragmatic approach in solving a set of common problems engineers and technicians encounter when processing signals. In writing it, the author drew on his vast theoretical and practical experience in the field to provide a quick-solution manual for technicians and engineers, offering field-tested solutions to most problems engineers can encounter. At the same time, the book delineates the basic concepts and applied mathematics underlying each solution so that readers can go deeper into the theory to gain a better idea of the solution’s limitations and potential pitfalls, and thus tailor the best solution for the specific engineering application. Uniquely, Statistical signal processing in Engineering can also function as a textbook for engineering graduates and post-graduates. Dr. Spagnolini, who has had a quarter of a century of experience teaching graduate-level courses in digital and statistical signal processing methods, provides a detailed axiomatic presentation of the conceptual and mathematical foundations of statistical signal processing that will challenge students’ analytical skills and motivate them to develop new applications on their own, or better understand the motivation underlining the existing solutions. Throughout the book, some real-world examples demonstrate how powerful a tool statistical signal processing is in practice across a wide range of applications. Takes an interdisciplinary approach, integrating basic concepts and tools for statistical signal processing Informed by its author’s vast experience as both a practitioner and teacher Offers a hands-on approach to solving problems in statistical signal processing Covers a broad range of applications, including communication systems, machine learning, wavefield and array processing, remote sensing, image filtering and distributed computations Features numero

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Mobile adaptive networks for pursuing multiple targets 40

Mobile adaptive networks for pursuing multiple targets

引用

40th IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2015

作者： Lin, May Zar Murthi, Manohar N. Premaratne, Kamal Department of Electrical and Computer Engineering University of Miami Coral GablesFL United States

ISBN: (纸本)9781467369978

We examine the design of self-organizing mobile adaptive networks with multiple targets in which the network nodes form distinct clusters to learn about and purse multiple targets, all while moving in a cohesive collision-free manner. We build upon previous distributed diffusion-based adaptive learning networks that focused on a single target to examine the case with multiple targets in which the nodes do not know the number of targets, and exchange local information with their neighbors in their learning objectives. In particular, we design a method allowing the nodes to switch the target they are tracking thereby engendering the formation of distinct stable learning groups that can split up and purse their distinct targets over time. We provide analytical mean stability and steady state mean-square deviation results along with simulations that demonstrate the efficacy of the proposed method. © 2015 IEEE.

关键词： adaptive networks diffusion adaptation distributed signal processing mobility self-organization

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distributed Kalman Filtering with quantized sensing state 40

Distributed Kalman Filtering with quantized sensing state

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40th IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2015

作者： Li, Di Kar, Soummya Cui, Shuguang Dept. of ECE Texas AandM University College StationTX United States Dept. of ECE Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9781467369978

This paper studies a Quantized Gossip-based Interactive Kalman Filtering (QGIKF) algorithm implemented in a wireless sensor network, where the sensors exchange their quantized states with neighbors via inter-sensor communications. We show that with the information loss due to quantization, the network can still achieve weak consensus, i.e., the estimation error variance sequence at a randomly selected sensor can converge weakly (in distribution) to a unique invariant measure. To prove the weak convergence, we first interpret the error variance sequence evolution as the interacting particle, then formulate the sequence as a Random Dynamical System (RDS), and finally prove that it is stochastically bounded. © 2015 IEEE.

关键词： distributed signal processing gossip Kalman filter quantization

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Cooperative Estimation in Heterogeneous Populations

Cooperative Estimation in Heterogeneous Populations

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45th Asilomar Conference on signals, Systems and Computers (ASILOMAR)

作者： Bean, Andrew J. Singer, Andrew C. Univ Illinois Urbana IL 61801 USA

ISBN: (纸本)9781467303231

We consider the problem of cooperative distributed estimation within a network of heterogeneous agents. We begin with 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. However, the agents of the population can be categorized into a small number of subgroups, where within each group the agents all have identical Bernoulli parameters. We present an algorithm for cooperative estimation in this setting which allows each agent's estimate to asymptotically converge to the correct value. We show how our technique can be applied in other settings, such as in heterogeneous least mean squares filter populations. Finally, we present simulation results showing the benefit of our technique, and compare it to noncooperative parameter estimation in a Bernoulli population.

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

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Programming signal processing Applications on Heterogeneous Wireless Sensor Platforms

Programming Signal Processing Applications on Heterogeneous ...

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5th IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems - Technology and Applications (IDAACS)

作者： Buondonno, Luigi Fortino, Giancarlo Galzarano, Stefano Giannantonio, Roberta Giordano, Antonio Gravina, Raffaele Guerrieri, Antonio Univ Calabria Dept Elect Informat & Syst DEIS I-87036 Arcavacata Di Rende CS Italy Telecom Italia TILAB Turin Italy WSN Lab Telecom Italia Berkeley CA 94704 USA

ISBN: (纸本)9781424448814

This paper proposes the SPINE frameworks (SPINE1.x and SPINE2) for the programming of signal processing applications on heterogeneous wireless sensor platforms. In particular, two integrable approaches based on the proposed frameworks are described that allow to develop applications for wireless body sensor networks (WBSNs) constituted by heterogeneous sensor nodes. The approaches are exemplified through a human activity recognition system based on a WBSN composed of two types of sensor nodes, heterogeneous with respect to base software and hardware.

关键词： Wireless body sensor networks software development methodology task-oriented programming distributed signal processing SPINE

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ENERGY-VS-PERFORMANCE TRADE-OFFS IN SPEECH ENHANCEMENT IN WIRELESS ACOUSTIC SENSOR NETWORKS 23

ENERGY-VS-PERFORMANCE TRADE-OFFS IN SPEECH ENHANCEMENT IN WI...

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23rd European signal processing Conference (EUSIPCO)

作者： Arce, Fernando de la Hucha Rosas, Fernando Moonen, Marc Verhelst, Marian Bertrand, Alexander Katholieke Univ Leuven Dept Elect Engn ESAT STADIUS Kasteelpk Arenberg 10 B-3001 Leuven Belgium Katholieke Univ Leuven Dept Elect Engn ESAT MICAS Kasteelpk Arenberg 10 B-3001 Leuven Belgium

ISBN: (纸本)9780992862633

distributed algorithms allow wireless acoustic sensor networks (WASNs) to divide the computational load of signal processing tasks, such as speech enhancement, among the sensor nodes. However, current algorithms focus on performance optimality, oblivious to the energy constraints that battery-powered sensor nodes usually face. To extend the lifetime of the network, nodes should be able to dynamically scale down their energy consumption when decreases in performance are tolerated. In this paper we study the relationship between energy and performance in the DANSE algorithm applied to speech enhancement. We propose two strategies that introduce flexibility to adjust the energy consumption and the desired performance. To analyze the impact. of these strategies we combine an energy model with simulations. Results show that the energy consumption can be substantially reduced depending on the tolerated decrease in performance. This shows significant potential for extending the network lifetime using dynamic system reconfiguration.

关键词： Dynamic system reconfiguration distributed signal processing wireless acoustic sensor networks

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