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Sep 21, 2013
09/13

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Wee Peng Tay

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We consider the decentralized binary hypothesis testing problem in networks with feedback, where some or all of the sensors have access to compressed summaries of other sensors' observations. We study certain two-message feedback architectures, in which every sensor sends two messages to a fusion center, with the second message based on full or partial knowledge of the first messages of the other sensors. We also study one-message feedback architectures, in which each sensor sends one message...

Source: http://arxiv.org/abs/1108.6121v1

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3.0

Jun 30, 2018
06/18

by
Wee Peng Tay

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We consider a multihypothesis social learning problem in which an agent has access to a set of private observations and chooses an opinion from a set of experts to incorporate into its final decision. To model individual biases, we allow the agent and experts to have general loss functions and possibly different decision spaces. We characterize the loss exponents of both the agent and experts, and provide an asymptotically optimal method for the agent to choose the best expert to follow. We...

Topics: Mathematics, Computing Research Repository, Information Theory

Source: http://arxiv.org/abs/1403.4011

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3.0

Jun 30, 2018
06/18

by
Wuhua Hu; Wee Peng Tay

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We propose a multi-hop diffusion strategy for a sensor network to perform distributed least mean-squares (LMS) estimation under local and network-wide energy constraints. At each iteration of the strategy, each node can combine intermediate parameter estimates from nodes other than its physical neighbors via a multi-hop relay path. We propose a rule to select combination weights for the multi-hop neighbors, which can balance between the transient and the steady-state network mean-square...

Topics: Mathematics, Computing Research Repository, Information Theory, Optimization and Control

Source: http://arxiv.org/abs/1407.6490

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Jun 27, 2018
06/18

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Wuqiong Luo; Wee Peng Tay; Mei Leng

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The goal of an infection source node (e.g., a rumor or computer virus source) in a network is to spread its infection to as many nodes as possible, while remaining hidden from the network administrator. On the other hand, the network administrator aims to identify the source node based on knowledge of which nodes have been infected. We model the infection spreading and source identification problem as a strategic game, where the infection source and the network administrator are the two...

Topics: Computing Research Repository, Social and Information Networks

Source: http://arxiv.org/abs/1504.04796

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70

Sep 21, 2013
09/13

by
Wuqiong Luo; Wee Peng Tay; Mei Leng

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Identifying the infection sources in a network, including the index cases that introduce a contagious disease into a population network, the servers that inject a computer virus into a computer network, or the individuals who started a rumor in a social network, plays a critical role in limiting the damage caused by the infection through timely quarantine of the sources. We consider the problem of estimating the infection sources and the infection regions (subsets of nodes infected by each...

Source: http://arxiv.org/abs/1204.0354v2

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50

Sep 18, 2013
09/13

by
Wee Peng Tay; John Tsitsiklis; Moe Win

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We consider the problem of decentralized detection in a network consisting of a large number of nodes arranged as a tree of bounded height, under the assumption of conditionally independent, identically distributed observations. We characterize the optimal error exponent under a Neyman-Pearson formulation. We show that the Type II error probability decays exponentially fast with the number of nodes, and the optimal error exponent is often the same as that corresponding to a parallel...

Source: http://arxiv.org/abs/0803.2337v1

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6.0

Jun 30, 2018
06/18

by
Yuan Wang; Wee Peng Tay; Wuhua Hu

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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, regardless of the inter-cluster cooperation weights. In addition, the proposed strategy is able to...

Topics: Systems and Control, Computing Research Repository

Source: http://arxiv.org/abs/1703.01888

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3.0

Jun 30, 2018
06/18

by
Wuhua Hu; Wee Peng Tay; Athul Harilal; Gaoxi Xiao

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We study the problem of identifying a single infection source in a network under the susceptible-infected-recovered-infected (SIRI) model. We describe the infection model via a state-space model, and utilizing a state propagation approach, we derive an algorithm known as the heterogeneous infection spreading source (HISS) estimator, to infer the infection source. The HISS estimator uses the observations of node states at a particular time, where the elapsed time from the start of the infection...

Topics: Physics, Mathematics, Physics and Society, Computing Research Repository, Social and Information...

Source: http://arxiv.org/abs/1410.2995

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Sep 23, 2013
09/13

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Mei Leng; Wee Peng Tay; Tony Q. S. Quek

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We consider the problem of sensor localization in a wireless network in a multipath environment, where time and angle of arrival information are available at each sensor. We propose a distributed algorithm based on belief propagation, which allows sensors to cooperatively self-localize with respect to one single anchor in a multihop network. The algorithm has low overhead and is scalable. Simulations show that although the network is loopy, the proposed algorithm converges, and achieves good...

Source: http://arxiv.org/abs/1109.5770v1

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3.0

Jun 30, 2018
06/18

by
Mei Leng; Wee Peng Tay; Tony Q. S. Quek; Hyundong Shin

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We consider the problem of estimating local sensor parameters, where the local parameters and sensor observations are related through linear stochastic models. Sensors exchange messages and cooperate with each other to estimate their own local parameters iteratively. We study the Gaussian Sum-Product Algorithm over a Wireless Network (gSPAWN) procedure, which is based on belief propagation, but uses fixed size broadcast messages at each sensor instead. Compared with the popular diffusion...

Topics: Systems and Control, Multiagent Systems, Computing Research Repository

Source: http://arxiv.org/abs/1404.3145

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5.0

Jun 30, 2018
06/18

by
Wenjie Xu; Francois Quitin; Mei Leng; Wee Peng Tay; Sirajudeen G. Razul

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We propose a novel distributed expectation maximization (EM) method for non-cooperative RF device localization using a wireless sensor network. We consider the scenario where few or no sensors receive line-of-sight signals from the target. In the case of non-line-of-sight signals, the signal path consists of a single reflection between the transmitter and receiver. Each sensor is able to measure the time difference of arrival of the target's signal with respect to a reference sensor, as well as...

Topics: Mathematics, Computing Research Repository, Information Theory

Source: http://arxiv.org/abs/1408.3195

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Jun 26, 2018
06/18

by
Jack Ho; Wee Peng Tay; Tony Q. S. Quek; Edwin K. P. Chong

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We study a tandem of agents who make decisions about an underlying binary hypothesis, where the distribution of the agent observations under each hypothesis comes from an uncertainty class. We investigate both decentralized detection rules, where agents collaborate to minimize the error probability of the final agent, and social learning rules, where each agent minimizes its own local minimax error probability. We then extend our results to the infinite tandem network, and derive necessary and...

Topics: Computing Research Repository, Mathematics, Information Theory

Source: http://arxiv.org/abs/1501.05847