IEEE Transactions on Signal and Information Processing over Networks

Issue 2 • June 2016

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Displaying Results 1 - 14 of 14
  • Table of Contents

    Publication Year: 2016, Page(s): C1
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  • IEEE Transactions on Signal and Information Processing over Networks publication information

    Publication Year: 2016, Page(s): C2
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  • Distributed Detection With Vector Quantizer

    Publication Year: 2016, Page(s):105 - 119
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (637 KB) | HTML iconHTML

    Motivated by distributed inference over big datasets problems, we study multiterminal distributed inference problems when each terminal employs vector quantizer. The use of vector quantizer enables us to relax the conditional independence assumption normally used in the distributed detection with scalar quantizer scenarios. We first consider a case of practical interest in which each terminal is a... View full abstract»

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  • NEXT: In-Network Nonconvex Optimization

    Publication Year: 2016, Page(s):120 - 136
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (682 KB) | HTML iconHTML

    We study nonconvex distributed optimization in multiagent networks with time-varying (nonsymmetric) connectivity. We introduce the first algorithmic framework for the distributed minimization of the sum of a smooth (possibly nonconvex and nonseparable) function-the agents' sum-utility-plus a convex (possibly nonsmooth and nonseparable) regularizer. The latter is usually employed to enforce some st... View full abstract»

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  • Graph Signal Denoising via Trilateral Filter on Graph Spectral Domain

    Publication Year: 2016, Page(s):137 - 148
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3060 KB) | HTML iconHTML

    This paper presents a graph signal denoising method with the trilateral filter defined in the graph spectral domain. The original trilateral filter (TF) is a data-dependent filter that is widely used as an edge-preserving smoothing method for image processing. However, because of the data-dependency, one cannot provide its frequency domain representation. To overcome this problem, we establish the... View full abstract»

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  • Energy-Assisted Information Detection for Simultaneous Wireless Information and Power Transfer: Performance Analysis and Case Studies

    Publication Year: 2016, Page(s):149 - 159
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1185 KB) | HTML iconHTML

    In simultaneous wireless information and power transfer (SWIPT), practical receiver architectures consisting of an information receiver and an energy harvester have been proposed in place of an ideal receiver capable of performing two tasks simultaneously using the same circuits. In this paper, we present a novel receiver architecture design incorporating an interplay between the information recei... View full abstract»

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  • Principal Patterns on Graphs: Discovering Coherent Structures in Datasets

    Publication Year: 2016, Page(s):160 - 173
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4373 KB) | HTML iconHTML

    Graphs are now ubiquitous in almost every field of research. Recently, new research areas devoted to the analysis of graphs and data associated to their vertices have emerged. Focusing on dynamical processes, we propose a fast, robust, and scalable framework for retrieving and analyzing recurring patterns of activity on graphs. Our method relies on a novel type of multilayer graph that encodes the... View full abstract»

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  • Location of Things: Geospatial Tagging for IoT Using Time-of-Arrival

    Publication Year: 2016, Page(s):174 - 185
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2035 KB) | HTML iconHTML

    We develop a new algorithm for geospatial tagging for Internet-of-Things (IoT) type applications, which we denote as location-of-things (LoT). The underlying idea of LoT applications is to use low-cost off-the-shelf two-way time-of-arrival (TW-ToA) ranging devices to perform localization of tags. We first demonstrate how conventional TW-ToA localization algorithms may experience performance degrad... View full abstract»

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  • Node Dominance: Revealing Community and Core-Periphery Structure in Social Networks

    Publication Year: 2016, Page(s):186 - 199
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1278 KB) | HTML iconHTML

    This study relates the local property of node dominance to local and global properties of a network. Iterative removal of dominated nodes yields a distributed algorithm for computing a core-periphery decomposition of a social network, where nodes in the network core are seen to be essential in terms of network flow and global structure. Additionally, the connected components in the periphery give ... View full abstract»

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  • Data Denoising and Compression for Smart Grid Communication

    Publication Year: 2016, Page(s):200 - 214
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3486 KB) | HTML iconHTML

    A technique based on wavelet packet decomposition (WPD) is proposed for the analysis, denoising, and compression of power system data in the smart grid (SG) communication. WPD is an expansion of wavelet decomposition (WD) tree algorithm to a full binary tree. The main advantage of WPD is better signal representation by finding the best tree from a number of bases of the WPD. Thus, the wavelet pack... View full abstract»

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  • Extraction of Temporal Network Structures From Graph-Based Signals

    Publication Year: 2016, Page(s):215 - 226
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2402 KB) | HTML iconHTML

    A new framework to track the structure of temporal networks with a signal processing approach is introduced. The method is based on the duality between static networks and signals, obtained using a multidimensional scaling technique, that makes possible the study of the network structure from frequency patterns of the corresponding signals. In this paper, we propose an approach to identify structu... View full abstract»

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  • Information for Authors

    Publication Year: 2016, Page(s): 227
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  • Information for Authors

    Publication Year: 2016, Page(s):228 - 229
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  • IEEE Transactions on Signal and Information Processing over Networks

    Publication Year: 2016, Page(s): C3
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Aims & Scope

The IEEE Transactions on Signal and Information Processing over Networks publishes high-quality papers that extend the classical notions of processing of signals defined over vector spaces (e.g. time and space) to processing of signals and information (data) defined over networks, potentially dynamically varying. In signal processing over networks, the topology of the network may define structural relationships in the data, or may constrain processing of the data. Topics include distributed algorithms for filtering, detection, estimation, adaptation and learning, model selection, data fusion, and diffusion or evolution of information over such networks, and applications of distributed signal processing.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Petar Djuric
Stony Brook University, Electrical & Computer Engineering
Light Engineering, Room 245
Stony Brook, NY
11794-2350
USA
+1 631-632-8423
Fax: +1 631-632-8494
petar.djuric@stonybrook.edu