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IEEE Journal of Selected Topics in Signal Processing

Issue 3 • April 2017

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  • Frontcover

    Publication Year: 2017, Page(s): C1
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  • IEEE Journal of Selected Topics in Signal Processing publication information

    Publication Year: 2017, Page(s): C2
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  • Table of Contents

    Publication Year: 2017, Page(s): 445
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  • Blank Page

    Publication Year: 2017, Page(s): B446
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  • Introduction to the Issue on Cooperative Signal Processing for Heterogeneous and Multi-Task Wireless Sensor Networks

    Publication Year: 2017, Page(s):447 - 449
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  • Heterogeneous and Multitask Wireless Sensor Networks—Algorithms, Applications, and Challenges

    Publication Year: 2017, Page(s):450 - 465
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (736 KB) | HTML iconHTML

    Unlike traditional homogeneous single-task wireless sensor networks (WSNs), heterogeneous and multitask WSNs allow the cooperation among multiple heterogeneous devices dedicated to solving different signal processing tasks. Despite their heterogeneous nature and the fact that each device may solve a different task, the devices could still benefit from a collaboration between them to achieve a supe... View full abstract»

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  • Feature-Sharing in Cascade Detection Systems With Multiple Applications

    Publication Year: 2017, Page(s):466 - 478
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (651 KB) | HTML iconHTML

    Traditional distributed detection systems are often designed for a single target application. However, with the emergence of the Internet of Things paradigm, next-generation systems are expected to be a shared infrastructure for multiple applications. To this end, we propose a modular, cascade design for resource-efficient, multitask detection systems. Two (classes of) applications are considered ... View full abstract»

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  • Heterogeneous Sensor Data Fusion By Deep Multimodal Encoding

    Publication Year: 2017, Page(s):479 - 491
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1328 KB) | HTML iconHTML

    Heterogeneous sensor data fusion is a challenging field that has gathered significant interest in recent years. Two of these challenges are learning from data with missing values, and finding shared representations for multimodal data to improve inference and prediction. In this paper, we propose amultimodal data fusion framework, the deep multimodal encoder (DME), based on deep learning technique... View full abstract»

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  • Distributed Recursive Gaussian Processes for RSS Map Applied to Target Tracking

    Publication Year: 2017, Page(s):492 - 503
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1169 KB) | HTML iconHTML

    We propose a distributed recursive Gaussian process (drGP) regression framework for building received-signal-strength (RSS) map. The proposed framework adopts independent mobile devices in prescribed local areas to construct local RSS maps through recursive computation of the posterior distribution of the RSS on a fixed set of grids as training data gradually become available. The training input p... View full abstract»

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  • A Multitask Diffusion Strategy With Optimized Inter-cluster Cooperation

    Publication Year: 2017, Page(s):504 - 517
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1348 KB) | HTML iconHTML

    We consider a multitask estimation problem where nodes in a network are divided into several connected clusters, with each cluster performing a least-mean-squares estimation of a different random parameter vector. Inspired by the adapt-then-combine diffusion strategy, we propose a multitask diffusion strategy whose mean stability can be ensured whenever individual nodes are stable in the mean, reg... View full abstract»

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  • Multi-Task Wireless Sensor Network for Joint Distributed Node-Specific Signal Enhancement, LCMV Beamforming and DOA Estimation

    Publication Year: 2017, Page(s):518 - 533
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2259 KB) | HTML iconHTML

    We consider a multi-task wireless sensor network (WSN) where some of the nodes aim at applying a multi-channel Wiener filter to denoise their local sensor signals, whereas others aim at implementing a linearly constrained minimum variance beamformer to extract node-specific desired signals and cancel interfering signals, and again others aim at estimating the node-specific direction-of-arrival of ... View full abstract»

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  • Coordinated SLNR Based Precoding in Large-Scale Heterogeneous Networks

    Publication Year: 2017, Page(s):534 - 548
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (810 KB) | HTML iconHTML

    This paper focuses on the downlink of large-scale two-tier heterogeneous networks composed of a macrocell overlaid by microcell networks. Our interest is on the design of coordinated beamforming techniques that allow to mitigate the intercell interference. Particularly, we consider the case in which the coordinating base stations have imperfect knowledge of the channel state information. Under thi... View full abstract»

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  • Wireless Power Transfer for Distributed Estimation in Sensor Networks

    Publication Year: 2017, Page(s):549 - 562
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (600 KB) | HTML iconHTML

    This paper studies power allocation for distributed estimation of an unknown scalar random source in sensor networks with a multiple-antenna fusion center (FC), where wireless sensors are equipped with radio-frequency-based energy harvesting technology. The sensors' observation is locally processed by using an uncoded amplify-and-forward scheme. The processed signals are then sent to the FC, and a... View full abstract»

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  • Multitask Diffusion Adaptation Over Networks With Common Latent Representations

    Publication Year: 2017, Page(s):563 - 579
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5331 KB) | HTML iconHTML

    Online learning with streaming data in a distributed and collaborative manner can be useful in a wide range of applications. This topic has been receiving considerable attention in recent years with emphasis on both single-task and multitask scenarios. In single-task adaptation, agents cooperate to track an objective of common interest, while in multitask adaptation agents track multiple objective... View full abstract»

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  • Blank Page

    Publication Year: 2017, Page(s): B580
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  • IEEE Journal of Selected Topics in Signal Processing information for authors

    Publication Year: 2017, Page(s):581 - 582
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  • Introducing IEEE Collabratec

    Publication Year: 2017, Page(s): 583
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  • Become a published author in 4 to 6 weeks

    Publication Year: 2017, Page(s): 584
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  • IEEE Membership Can Help You Reach Your Personal and Professional Goals

    Publication Year: 2017, Page(s): 585
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  • IEEE Signal Processing Society Information

    Publication Year: 2017, Page(s): C3
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  • Blank Page

    Publication Year: 2017, Page(s): C4
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Aims & Scope

The Journal of Selected Topics in Signal Processing (J-STSP) solicits special issues on topics that cover the entire scope of the IEEE Signal Processing Society including the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief

Shrikanth (Shri) S. Narayanan
Viterbi School of Engineering 
University of Southern California
Los Angeles, CA 90089 USA
shri@sipi.usc.edu