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  Subjects -> ELECTRONICS (Total: 187 journals)
Showing 1 - 200 of 277 Journals sorted alphabetically
Acta Electronica Malaysia     Open Access  
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 7)
Advances in Electronics     Open Access   (Followers: 90)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Power Electronics     Open Access   (Followers: 38)
Advancing Microelectronics     Hybrid Journal  
Aerospace and Electronic Systems, IEEE Transactions on     Hybrid Journal   (Followers: 334)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 26)
Annals of Telecommunications     Hybrid Journal   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 9)
Archives of Electrical Engineering     Open Access   (Followers: 14)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 30)
Bioelectronics in Medicine     Hybrid Journal  
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 20)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 38)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 6)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 13)
BULLETIN of National Technical University of Ukraine. Series RADIOTECHNIQUE. RADIOAPPARATUS BUILDING     Open Access   (Followers: 1)
Bulletin of the Polish Academy of Sciences : Technical Sciences     Open Access   (Followers: 1)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 47)
China Communications     Full-text available via subscription   (Followers: 9)
Chinese Journal of Electronics     Hybrid Journal  
Circuits and Systems     Open Access   (Followers: 15)
Consumer Electronics Times     Open Access   (Followers: 5)
Control Systems     Hybrid Journal   (Followers: 293)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access  
Edu Elektrika Journal     Open Access   (Followers: 1)
Electrica     Open Access  
Electronic Design     Partially Free   (Followers: 117)
Electronic Markets     Hybrid Journal   (Followers: 7)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Electronics     Open Access   (Followers: 97)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 10)
Electronics For You     Partially Free   (Followers: 100)
Electronics Letters     Hybrid Journal   (Followers: 26)
Elkha : Jurnal Teknik Elektro     Open Access  
Embedded Systems Letters, IEEE     Hybrid Journal   (Followers: 55)
Energy Harvesting and Systems     Hybrid Journal   (Followers: 4)
Energy Storage Materials     Full-text available via subscription   (Followers: 3)
EPJ Quantum Technology     Open Access   (Followers: 1)
EURASIP Journal on Embedded Systems     Open Access   (Followers: 11)
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 10)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 1)
Geoscience and Remote Sensing, IEEE Transactions on     Hybrid Journal   (Followers: 205)
Haptics, IEEE Transactions on     Hybrid Journal   (Followers: 4)
IACR Transactions on Symmetric Cryptology     Open Access  
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 99)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 80)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 49)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 9)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 1)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 72)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 71)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 58)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 26)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 42)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 19)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 26)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 78)
IEEE Transactions on Signal and Information Processing over Networks     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 5)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access  
IET Microwaves, Antennas & Propagation     Hybrid Journal   (Followers: 35)
IET Nanodielectrics     Open Access  
IET Power Electronics     Hybrid Journal   (Followers: 55)
IET Smart Grid     Open Access  
IET Wireless Sensor Systems     Hybrid Journal   (Followers: 18)
IETE Journal of Education     Open Access   (Followers: 4)
IETE Journal of Research     Open Access   (Followers: 11)
IETE Technical Review     Open Access   (Followers: 13)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 70)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 35)
Informatik-Spektrum     Hybrid Journal   (Followers: 2)
Instabilities in Silicon Devices     Full-text available via subscription   (Followers: 1)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 13)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 18)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 11)
International Journal of Antennas and Propagation     Open Access   (Followers: 11)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 4)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 6)
International Journal of Control     Hybrid Journal   (Followers: 11)
International Journal of Electronics     Hybrid Journal   (Followers: 7)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 13)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 3)
International Journal of High Speed Electronics and Systems     Hybrid Journal  
International Journal of Hybrid Intelligence     Hybrid Journal  
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 16)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 10)
International Journal of Nanoscience     Hybrid Journal   (Followers: 1)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 4)
International Journal of Power Electronics     Hybrid Journal   (Followers: 25)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 10)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 4)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 6)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 3)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Journal of Artificial Intelligence     Open Access   (Followers: 11)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 32)
Journal of Electrical Bioimpedance     Open Access  
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 9)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 6)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
Journal of Engineered Fibers and Fabrics     Open Access   (Followers: 2)
Journal of Field Robotics     Hybrid Journal   (Followers: 3)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 173)
Journal of Information and Telecommunication     Open Access   (Followers: 1)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 3)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 10)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 10)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal  
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 3)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 11)
Journal of Nuclear Cardiology     Hybrid Journal  
Journal of Optoelectronics Engineering     Open Access   (Followers: 4)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 29)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 11)
Journal of Semiconductors     Full-text available via subscription   (Followers: 5)
Journal of Sensors     Open Access   (Followers: 26)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access  
Learning Technologies, IEEE Transactions on     Hybrid Journal   (Followers: 12)
Magnetics Letters, IEEE     Hybrid Journal   (Followers: 7)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
Nanotechnology Magazine, IEEE     Full-text available via subscription   (Followers: 41)
Nanotechnology, Science and Applications     Open Access   (Followers: 6)
Nature Electronics     Hybrid Journal   (Followers: 1)
Networks: an International Journal     Hybrid Journal   (Followers: 5)
Open Electrical & Electronic Engineering Journal     Open Access  
Open Journal of Antennas and Propagation     Open Access   (Followers: 9)
Optical Communications and Networking, IEEE/OSA Journal of     Full-text available via subscription   (Followers: 15)
Paladyn. Journal of Behavioral Robotics     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 2)
Problemy Peredachi Informatsii     Full-text available via subscription  
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Pulse     Full-text available via subscription   (Followers: 5)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 9)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 5)
Revue Méditerranéenne des Télécommunications     Open Access  
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 56)
Semiconductors and Semimetals     Full-text available via subscription   (Followers: 1)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Services Computing, IEEE Transactions on     Hybrid Journal   (Followers: 4)
Software Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 78)
Solid State Electronics Letters     Open Access  
Solid-State Circuits Magazine, IEEE     Hybrid Journal   (Followers: 13)
Solid-State Electronics     Hybrid Journal   (Followers: 9)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 3)
Technical Report Electronics and Computer Engineering     Open Access  
TELE     Open Access  
Telematique     Open Access  
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 9)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 6)
Ural Radio Engineering Journal     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access   (Followers: 1)
Wireless and Mobile Technologies     Open Access   (Followers: 6)
Wireless Power Transfer     Full-text available via subscription   (Followers: 4)
Women in Engineering Magazine, IEEE     Full-text available via subscription   (Followers: 11)
Електротехніка і Електромеханіка     Open Access  

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Similar Journals
Journal Cover
IEEE Transactions on Signal and Information Processing over Networks
Number of Followers: 12  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 2373-776X
Published by IEEE Homepage  [191 journals]
  • IEEE Transactions on Signal and Information Processing over Networks
           publication information
    • Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • IEEE Transactions on Signal and Information Processing over Networks
    • Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Graph-Based Compression for Distributed Particle Filters
    • Authors: Jun Ye Yu;Mark J. Coates;Michael G. Rabbat;
      Pages: 404 - 417
      Abstract: A key challenge in designing distributed particle filters is to minimize the communication overhead without compromising tracking performance. In this paper, we present two distributed particle filters that achieve robust performance with low communication overhead. The two filters construct a graph of the particles and exploit the graph Laplacian matrix in different manners to encode the particle log-likelihoods using a minimum number of coefficients. We validate their performance via simulations with very low communication overhead and provide a theoretical error bound for the presented filters.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Expander Recovery Performance of Bipartite Graphs With Girth Greater Than
           4
    • Authors: Weizhi Lu;Weiyu Li;Wei Zhang;Shu-Tao Xia;
      Pages: 418 - 427
      Abstract: Expander recovery is an iterative algorithm designed to recover sparse signals measured with binary matrices with linear complexity. In the paper, we study the expander recovery performance of the bipartite graph with girth greater than 4, which can be associated with a binary matrix with column correlations equal to either 0 or 1. For such a graph, expander recovery is proved to achieve the same performance as the traditional basis pursuit recovery, as the signal is dissociated. Compared to random graphs widely used for expander recovery, the graph we study tends to present better empirical performance. Furthermore, its special structure enables reducing the iteration number of expander recovery from O(n log k) times to exactly k times in serial recovery, and from O(log k) times to exactly one time in parallel recovery.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Distributed Robust Bayesian Filtering for State Estimation
    • Authors: Junhao Hua;Chunguang Li;
      Pages: 428 - 441
      Abstract: We study the problem of distributed filtering for state space models over networks, which aims to collaboratively estimate the states by a network of nodes. Most of existing works on this problem assume that both process and measurement noises are Gaussian and their covariances are known in advance. In some cases, this assumption breaks down and no longer holds. In this paper, we consider the case that both process and measurement noise covariances are unknown. A few related works have studied this problem. However, these works consider the situation of centralized processing, and they only derive smoothers which are not suitable for online processing in a network. Instead, this paper presents a novel robust Bayesian filter with unknown process and measurement noise covariances over sensor networks, which is distributed and online. A novel Bayesian model is formulated for a modified state space model. This Bayesian model is capable of dealing with outliers and heavy-tailed noises and improving the robustness of the filter to these non-Gaussian noises. Using this model, we first propose a novel centralized algorithm for the robust Bayesian filtering based on variational Bayesian methods. Then, we extend it to the distributed scenario based on the alternating direction method of multipliers (ADMM) technique. The proposed algorithm can simultaneously estimate the states and process/measurement noise covariances. Simulations on a target tracking problem are given to verify the effectiveness of the proposed model and algorithm. The results demonstrate that the proposed algorithm performs much better than the standard Kalman filter and as good as the corresponding centralized algorithm in the presence of outliers.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • On the Q-Linear Convergence of Distributed Generalized ADMM Under
           Non-Strongly Convex Function Components
    • Authors: Marie Maros;Joakim Jaldén;
      Pages: 442 - 453
      Abstract: Solving optimization problems in multi-agent networks where each agent only has partial knowledge of the problem has become an increasingly important problem. In this paper, we consider the problem of minimizing the sum of n convex functions. We assume that each function is only known by one agent. We show that generalized distributed alternating direction method of multipliers (ADMM) converges Q-linearly to the solution of the mentioned optimization problem if the overall objective function is strongly convex but the functions known by each agent are allowed to be only convex. Establishing Q-linear convergence allows for tracking statements that cannot be made if only R-linear convergence is guaranteed. In other words, in scenarios in which the objective functions are time-varying at the same scale as the algorithm is updated R-linear convergence is typically insufficient. Further, we establish the equivalence between generalized distributed ADMM and proximal exact first-order algorithm (P-EXTRA) for a sub-set of mixing matrices. This equivalence yields insights in the convergence of P-EXTRA when overshooting to accelerate convergence.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Position-Constrained Stochastic Inference for Cooperative Indoor
           Localization
    • Authors: Rico Mendrzik;Gerhard Bauch;
      Pages: 454 - 468
      Abstract: We address the problem of distributed cooperative localization in wireless networks, i.e., nodes without prior position knowledge (agents) wish to determine their own positions. In non-cooperative approaches, positioning is only based on information from reference nodes with known positions (anchors). However, in cooperative positioning, information from other agents is considered as well. Cooperative positioning requires encoding of the uncertainties of agents' positions. To cope with that demand, we consider stochastic inference for localization, which inherently takes the position uncertainties of agents into consideration. Generally, stochastic inference comes at the expense of high costs in terms of computation and information exchange. To relax the requirements of inference algorithms, we propose the framework of position-constrained stochastic inference, in which we first confine the positions of nodes to constrained regions. These regions assist inference algorithms to concentrate on the important areas of the sample space rather than the entire sample space. In contrast to many state-of-the-art approaches, our approach does not require prior knowledge on the positions of agents. We show through simulations that increased localization accuracy, reduced computational complexity, and quicker convergence can be achieved when compared to state-of-the-art non-constrained inference algorithms.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Automatic Modulation Classification Using Convolutional Neural Network
           With Features Fusion of SPWVD and BJD
    • Authors: Zufan Zhang;Chun Wang;Chenquan Gan;Shaohui Sun;Mengjun Wang;
      Pages: 469 - 478
      Abstract: Automatic modulation classification (AMC) is becoming increasingly important in spectrum monitoring and cognitive radio. However, most existing modulation classification algorithms neglect the complementarities between different features and the importance of features fusion. To remedy these flaws, this paper presents a scheme of features fusion for AMC using convolutional neural network (CNN). The approach attempts to fuse different images and handcrafted features of signals to obtain more discriminating features. First, eight handcrafted features and different images features are both extracted. In the latter, signals are converted into two kinds of time-frequency images by smooth pseudo-wigner-ville distribution and Born-Jordan distribution, and a fine-tuned CNN model is utilized to extract image features. Second, the joint features are formed by combination of each of image and handcrafted features, and a multimodality fusion model is applied to fuse the joint features to yield further improvement. Finally, simulation results reveal the superior performance of the proposed scheme. It is worth mentioning that the classification accuracy can reach 92.5% with signal-to-noise ratio at -4 dB.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Asynchronous Online Learning in Multi-Agent Systems With Proximity
           Constraints
    • Authors: Amrit Singh Bedi;Alec Koppel;Ketan Rajawat;
      Pages: 479 - 494
      Abstract: We consider the problem of distributed learning from sequential data via online convex optimization. A multi-agent system is considered where each agent has a private objective but is willing to cooperate in order to minimize the network cost, which is the sum of local cost functions. Different from the classical distributed settings, where the agents coordinate through the use of consensus constraints, we allow the neighboring agent actions to be related via a non-linear proximity function. A decentralized saddle point algorithm is proposed that is capable of handling gradient delays arising from computational issues. The proposed online asynchronous algorithm is analyzed under adversarial settings by developing bounds on the regret of O(√T), which measures the cumulative loss incurred by the online algorithm against a clairvoyant, and network discrepancy of O(T3/4), which measures the cumulative constraint violation or agent disagreement. By allowing the agents to utilize stale gradient information, the proposed algorithm embraces the nuances of distributed learning and serves to be the first distributed online algorithm that can handle adversarial delays. A modified saddle point algorithm is also proposed that explicitly forces the agents to agree as per the constraint function resulting in zero network discrepancy while incurring a slightly higher regret. To showcase the efficacy of the proposed asynchronous algorithm, a spatially correlated random field estimation problem is formulated and solved. Additionally, an application of vision-based target localization with moving cameras demonstrates the benefits of this approach in practice.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • On the Distributed Method of Multipliers for Separable Convex Optimization
           Problems
    • Authors: Thomas Sherson;Richard Heusdens;W. Bastiaan Kleijn;
      Pages: 495 - 510
      Abstract: In this paper, we present a novel method for convex optimization in distributed networks called the distributed method of multipliers (DMM). The proposed method is based on a combination of a particular dual lifting and classic monotone operator splitting approaches to produce an algorithm with guaranteed asymptotic convergence in undirected networks. The proposed method allows any separable convex problem with linear constraints to be solved in undirected networks. In contrast to typical distributed approaches, the structure of the network does not restrict the types of problems that can be solved. Furthermore, the solver can be applied to general separable problems, those with separable convex objectives and constraints, via the use of an additional primal lifting approach. Finally, we demonstrate the use of DMM in solving a number of classic signal processing problems including beamforming, channel capacity maximization and portfolio optimization.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Consensus-Based Distributed Discrete Optimal Transport for Decentralized
           Resource Matching
    • Authors: Rui Zhang;Quanyan Zhu;
      Pages: 511 - 524
      Abstract: Optimal transport has been extensively used in resource matching to promote the efficiency of resource usages by matching sources to targets. However, it requires a significant amount of computations and storage spaces for large-scale problems. In this paper, we take a consensus-based approach to decentralize discrete optimal transport problems and develop fully distributed algorithms with alternating direction method of multipliers. We show that our algorithms guarantee certain levels of efficiency and privacy besides the distributed nature. We further derive primal and dual algorithms by exploring the primal and dual problems of discrete optimal transport with linear utility functions and prove the equivalence between them. We verify the convergence, online adaptability, and the equivalence between the primal algorithm and the dual algorithm with numerical experiments. Our algorithms reflect the bargaining between sources and targets on the amounts and prices of transferred resources and reveal an averaging principle which can be used to regulate resource markets and improve resource efficiency.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Using Social Network Information in Community-Based Bayesian Truth
           Discovery
    • Authors: Jielong Yang;Junshan Wang;Wee Peng Tay;
      Pages: 525 - 537
      Abstract: We investigate the problem of truth discovery based on opinions from multiple agents (who may be unreliable or biased) that form a social network. We consider the case where agents' reliabilities or biases are correlated if they belong to the same community, which defines a group of agents with similar opinions regarding a particular event. An agent can belong to different communities for different events, and these communities are unknown a priori. We incorporate knowledge of the agents' social network in our truth discovery framework and develop Laplace variational inference methods to estimate agents' reliabilities, communities, and the event states. We also develop a stochastic variational inference method to scale our model to large social networks. Simulations and experiments on real data suggest that when observations are sparse, our proposed methods perform better than several other inference methods, including majority voting, TruthFinder, AccuSim, the Confidence-Aware Truth Discovery method, the Bayesian classifier combination (BCC) method, and the community BCC method.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Adaptive Polling in Hierarchical Social Networks Using Blackwell Dominance
    • Authors: Sujay Bhatt;Vikram Krishnamurthy;
      Pages: 538 - 553
      Abstract: This paper presents adaptive polling algorithms and their analysis for social networks having a hierarchical influence structure. The adaptive polling problem on the social network is formulated as a partially observed Markov decision process (POMDP). Our main results exploit the structure of the polling problem to determine novel conditions for Blackwell dominance that arise in hierarchical social influence networks. The Blackwell dominance conditions enable the construction of myopic policies that provably upper bound the optimal policy of the POMDP for adaptive polling. Adaptive versions of intent polling and expectation polling are developed using Blackwell dominance, and they are inexpensive to implement. For polling problems not having a Blackwell dominance structure, the Le Cam deficiency is used to determine approximate Blackwell dominance; this is used to develop an adaptive version of the recently proposed Neighbourhood Expectation Polling algorithm. The proposed Blackwell dominance conditions also facilitate the comparison of Rényi divergence and Shannon capacity of more general channel structures that arise in polling hierarchical social influence networks. Numerical examples are provided to illustrate the adaptive polling policies with parameters estimated from YouTube data.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Blue-Noise Sampling on Graphs
    • Authors: Alejandro Parada-Mayorga;Daniel L. Lau;Jhony H. Giraldo;Gonzalo R. Arce;
      Pages: 554 - 569
      Abstract: In the area of graph signal processing, a graph is a set of nodes arbitrarily connected by weighted links; a graph signal is a set of scalar values associated with each node; and sampling is the problem of selecting an optimal subset of nodes from which a graph signal can be reconstructed. This paper proposes the use of spatial dithering on the vertex domain of the graph, as a way to conveniently find statistically good sampling sets. This is done establishing that there is a family of good sampling sets characterized on the vertex domain by a maximization of the distance between sampling nodes; in the Fourier domain, these are characterized by spectrums that are dominated by high frequencies referred to as blue-noise. The theoretical connection between blue-noise sampling on graphs and previous results in graph signal processing is also established, explaining the advantages of the proposed approach. Restricting our analysis to undirected and connected graphs, numerical tests are performed in order to compare the effectiveness of blue-noise sampling against other approaches.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Event-Triggered Distributed Multitarget Tracking
    • Authors: Lin Gao;Giorgio Battistelli;Luigi Chisci;
      Pages: 570 - 584
      Abstract: This paper focuses on reducing communication bandwidth and, consequently, energy consumption in the context of distributed multitarget tracking over a peer-to-peer sensor network. A consensus cardinalized probability hypothesis density (CCPHD) filter with event-triggered communication is developed by enforcing each node to broadcast its local information to the neighbors only when it is worth to, i.e., the node has gained a sufficient amount of information with respect to its latest broadcasting. To this end, each sensor node separately evaluates the discrepancies of the cardinality probability mass function (PMF) and of the spatial probability density function (PDF) between the current local posterior and the one recoverable from neighbors after the latest transmission. Then, each sensor node selectively sends the specific information on the multitarget distribution (i.e., the cardinality PMF or the spatial PDF or both) that is considered to be worth transmitting (i.e., such that the respective discrepancy exceeds a preset threshold). Two types of discrepancy measures, i.e., the Kullback-Leibler divergence and the Cauchy-Schwarz divergence, are investigated. The performance of the proposed event-triggered CCPHD filter is evaluated through simulation experiments.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Fusion Rules for Distributed Detection in Clustered Wireless Sensor
           Networks With Imperfect Channels
    • Authors: Sami Ahmed Aldalahmeh;Saleh O. Al-Jazzar;Des McLernon;Syed Ali Raza Zaidi;Mounir Ghogho;
      Pages: 585 - 597
      Abstract: In this paper, we investigate fusion rules for distributed detection in large random clustered wireless sensor networks with a three-tier hierarchy; the sensor nodes (SNs), the cluster heads (CHs), and the fusion center (FC). The CHs collect the SNs' local decisions and relay them to the FC, which then fuses them to reach the ultimate decision. The SN-CH and the CH-FC channels suffer from additive white Gaussian noise. In this context, we derive the optimal log-likelihood ratio (LLR) fusion rule, which turns out to be intractable. So, we develop a sub-optimal linear fusion rule (LFR) that weighs the cluster's data according to both its local detection performance and the quality of the communication channels. In order to implement it, we propose an approximate maximum likelihood based LFR (LFR-aML), which estimates the required parameters for the LFR. We also derive Gaussian-tail upper bounds for the detection and false alarms probabilities for the LFR. Furthermore, an optimal CH transmission power allocation strategy is developed by solving the Karush-Kuhn-Tucker conditions for the related optimization problem. Extensive simulations show that the LFR attains a detection performance near to that of the optimal LLR and confirms the validity of the proposed upper bounds. Moreover, when compared to equal power allocation, simulations show that our proposed power allocation strategy achieves a significant power saving at the expense of a small reduction in the detection performance.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
  • Decentralized Topology Reconfiguration in Multiphase Distribution Networks
    • Authors: Jingyuan Liu;Pirathayini Srikantha;
      Pages: 598 - 610
      Abstract: The cyber-physical nature of the modern power grid allows active power entities to exchange information signals with one another to make intelligent local actuation decisions. Exacting effective coordination amongst these cyber-enabled entities by way of strategic signal exchanges is essential for accommodating highly fluctuating power components (e.g., renewables, electric vehicles, etc.) that are becoming prevalent in today's electric grid. As such, in this paper, we present a novel decentralized topology reconfiguration algorithm for the distribution network (DN) that allows the system to adapt in real time to unexpected perturbations and/or congestions to restore balance in loads across the feeder and improve the DN voltage profile. For this, individual agents residing in DN buses iteratively exchange signals with neighbouring nodes to infer the current state (e.g., power balance and voltage) of the system and utilize this information to make local line switching decisions. Strong convergence properties and optimality conditions of the proposed algorithm are established via theoretical studies evoking potential games and discrete concavity. Comparative simulation studies conducted on realistic DNs showcase the practical properties of the proposed algorithm.
      PubDate: Sept. 2019
      Issue No: Vol. 5, No. 3 (2019)
       
 
 
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