Volume 7 Issue 2 • April 2013
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Table of Contents
Publication Year: 2013, Page(s):C1 - C4|
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IEEE Journal of Selected Topics in Signal Processing publication information
Publication Year: 2013, Page(s): C2|
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Introduction to the issue on adaptation and learning over complex networks
Publication Year: 2013, Page(s):161 - 162
Cited by: Papers (1) -
Distributed Pseudo-Gossip Algorithm and Finite-Length Computational Codes for Efficient In-Network Subspace Projection
Publication Year: 2013, Page(s):163 - 174
Cited by: Papers (6)In this paper, we design a practical power-efficient algorithm for Wireless Sensor Networks (WSN) in order to obtain, in a distributed manner, the projection of an observed sampled spatial field on a subspace of lower dimension. This is an important problem that is motivated in various applications where there are well defined subspaces of interest (e.g., spectral maps in cognitive radios). As opp... View full abstract»
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Diffusion of Cooperative Behavior in Decentralized Cognitive Radio Networks With Selfish Spectrum Sensors
Publication Year: 2013, Page(s):175 - 183
Cited by: Papers (15)This work investigates the diffusion of cooperative behavior over time in a decentralized cognitive radio network with selfish spectrum-sensing users. The users can individually choose whether or not to participate in cooperative spectrum sensing, in order to maximize their individual payoff defined in terms of the sensing false-alarm rate and transmit energy expenditure. The system is modeled as ... View full abstract»
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Edge Balance Ratio: Power Law From Vertices to Edges in Directed Complex Network
Publication Year: 2013, Page(s):184 - 194
Cited by: Papers (2)Power law distribution is common in real-world networks including online social networks. Many studies on complex networks focus on the characteristics of vertices, which are always proved to follow the power law. However, few researches have been done on edges in directed networks. In this paper, edge balance ratio is firstly proposed to measure the balance property of edges in directed networks.... View full abstract»
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On the Genericity Properties in Distributed Estimation: Topology Design and Sensor Placement
Publication Year: 2013, Page(s):195 - 204
Cited by: Papers (29)In this paper, we consider distributed estimation of linear, discrete-time dynamical systems monitored by a network of agents. We require the agents to exchange information with their neighbors only once per dynamical system time-scale and study the network topology sufficient for distributed observability. To this aim, we provide a novel measurement-based agent classification: Type- α,β, and γ, w... View full abstract»
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Distributed Pareto Optimization via Diffusion Strategies
Publication Year: 2013, Page(s):205 - 220
Cited by: Papers (87)We consider solving multi-objective optimization problems in a distributed manner by a network of cooperating and learning agents. The problem is equivalent to optimizing a global cost that is the sum of individual components. The optimizers of the individual components do not necessarily coincide and the network therefore needs to seek Pareto optimal solutions. We develop a distributed solution t... View full abstract»
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Distributed Random Projection Algorithm for Convex Optimization
Publication Year: 2013, Page(s):221 - 229
Cited by: Papers (86)Random projection algorithm is of interest for constrained optimization when the constraint set is not known in advance or the projection operation on the whole constraint set is computationally prohibitive. This paper presents a distributed random projection algorithm for constrained convex optimization problems that can be used by multiple agents connected over a time-varying network, where each... View full abstract»
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Designing Games for Distributed Optimization
Publication Year: 2013, Page(s):230 - 242
Cited by: Papers (97)The central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to a given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent's control law on the least amount of information possible. This paper focuses on achieving this goal using the fie... View full abstract»
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A Distributed Subgradient Method for Dynamic Convex Optimization Problems Under Noisy Information Exchange
Publication Year: 2013, Page(s):243 - 256
Cited by: Papers (23)We consider a convex optimization problem for non-hierarchical agent networks where each agent has access to a local or private time-varying function, and the network-wide objective is to find a time-invariant minimizer of the sum of these functions, provided that such a minimizer exists. Problems of this type are common in dynamic systems where the objective function is time-varying because of, f... View full abstract»
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Trading off Complexity With Communication Costs in Distributed Adaptive Learning via Krylov Subspaces for Dimensionality Reduction
Publication Year: 2013, Page(s):257 - 273
Cited by: Papers (23)In this paper, the problem of dimensionality reduction in adaptive distributed learning is studied. We consider a network obeying the ad-hoc topology, in which the nodes sense an amount of data and cooperate with each other, by exchanging information, in order to estimate an unknown, common, parameter vector. The algorithm, to be presented here, follows the set-theoretic estimation rationale; i.e.... View full abstract»
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A Gossip Method for Optimal Consensus on a Binary State From Binary Actions
Publication Year: 2013, Page(s):274 - 283
Cited by: Papers (14)In this paper, we study the problem of distributed hypothesis testing in cooperative networks of agents over a given undirected graph. All the agents try to reach consensus on the state of nature based on their private signals and the binary actions of their neighbors. This is a challenging problem because the exchanged information of the agents regarding their observations used for making decisio... View full abstract»
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Toward Resource-Optimal Consensus Over the Wireless Medium
Publication Year: 2013, Page(s):284 - 295
Cited by: Papers (11)We carry out a comprehensive study of the resource cost of averaging consensus in wireless networks. Most previous approaches suppose a graphical network, which abstracts away crucial features of the wireless medium, and measure resource consumption only in terms of the total number of transmissions required to achieve consensus. Under a path-loss model, we study the resource requirements of conse... View full abstract»
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Continuous-Time Distributed Observers With Discrete Communication
Publication Year: 2013, Page(s):296 - 304
Cited by: Papers (21)This work presents a distributed algorithm for observer design for linear continuous-time systems. We assume the dynamical system to be partitioned into disjoint areas, and we let each area be equipped with a control center. Each control center knows local dynamics, collects local observations, performs local computation, and communicates with neighboring control centers at discrete times. For our... View full abstract»
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Learning in Hierarchical Social Networks
Publication Year: 2013, Page(s):305 - 317
Cited by: Papers (4)We study a social network consisting of agents organized as a hierarchical <i>M</i>-ary rooted tree, common in enterprise and military organizational structures. The goal is to aggregate information to solve a binary hypothesis testing problem. Each agent at a leaf of the tree, and only such an agent, makes a direct measurement of the underlying true hypothesis. The leaf agent then gen... View full abstract»
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A Generalized Markov Graph Model: Application to Social Network Analysis
Publication Year: 2013, Page(s):318 - 332
Cited by: Papers (14)In this paper we propose a generalized Markov Graph model for social networks and evaluate its application in social network synthesis, and in social network classification. The model reveals that the degree distribution, the clustering coefficient distribution as well as a newly discovered feature, a crowding coefficient distribution, are fundamental to characterizing a social network. The applic... View full abstract»
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Mis-Information Removal in Social Networks: Constrained Estimation on Dynamic Directed Acyclic Graphs
Publication Year: 2013, Page(s):333 - 346
Cited by: Papers (7)A key issue in the multi agent state estimation presented in social networks is the inadvertent multiple re-use of data also known as mis-information propagation or data incest. We formulate this mis-information propagation in a graph theoretic setting and give a necessary and sufficient conditions on the topology of information flow network so that the underlying state can be estimated optimally.... View full abstract»
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The Effect of Exogenous Inputs and Defiant Agents on Opinion Dynamics With Local and Global Interactions
Publication Year: 2013, Page(s):347 - 357
Cited by: Papers (3)Most of the conventional models for opinion dynamics mainly account for a fully local influence, where myopic agents decide their actions after they interact with other agents that are adjacent to them. For example, in the case of social interactions, this includes family, friends, and other immediate strong social ties. The model proposed in this paper embodies a global influence as well where by... View full abstract»
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Reaching Consensus With Increasing Information
Publication Year: 2013, Page(s):358 - 369
Cited by: Papers (11)This paper focuses on a model of opinion formation over networks with continuously flowing new information and studies the relationship between the network and information structures and agents' ability to reach agreement. At each time period, agents receive private signals in addition to observing the beliefs held by their neighbors in a network. Each agent then updates its belief by aggregating ... View full abstract»
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IEEE Journal of Selected Topics in Signal Processing information for authors
Publication Year: 2013, Page(s):370 - 371|
PDF (133 KB)
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J-STSP call for special issue proposals
Publication Year: 2013, Page(s): 372|
PDF (765 KB)
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IEEE Signal Processing Society Information
Publication Year: 2013, Page(s): C3|
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Aims & Scope
The scope of the IEEE Journal of Selected Topics in Signal Processing (JSTSP) is the Field of Interest of the IEEE Signal Processing Society: “The theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques. The term “signal” includes audio, video, speech, image, communication, geophysical, sonar, radar, medical, musical, and other signals.” The format of the journal allows the exploration, in depth, of a signal processing topic. This format allows the Society to not only provide issues on more mature signal processing topical areas, but also to explore new areas, particularly those at the nexus of other engineering disciplines that are dependent upon signal processing (e.g., biomedical engineering; language), as well as those not traditionally part of the engineering landscape (e.g., genetics; security; atmospheric prediction).
Meet Our Editors
Editor-in-Chief
Lina Karam
School of Electrical, Computer, and Energy Engineering
Arizona State University
Tempe, AZ 85287-5706 USAkaram@asu.edu