Add to ORKGThe problem of optimal node density for ad hoc sensor networks deployed for making inferences about two dimensional correlated random fields is considered. Using a symmetric first order conditional autoregressive Gauss-Markov random field model, large deviations results are used to character-ize the asymptotic per-node information gained from the array. This result then allows an analysis ofthe node density that maximizes the information under an energy constraint, yielding insights into the trade-offs among the information, density and energy. 1
© 2013 IEEE. This paper addresses the problem of selecting the most informative sensor locations out...
In this paper, we study the critical sensor density for partial connectivity of a large area sensor ...
International audienceAs sensors are energy constrained devices, one challenge in wireless sensor ne...
Abstract—Using large deviations results that characterize the amount of information per node on a tw...
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject t...
The detection of hidden two-dimensional Gauss-Markov random fields us-ing sensor networks is conside...
Abstract — The problem of maximizing detection performance subject to an energy constraint is analyz...
International audienceWe consider a sensor network which observes a spatially correlated random fiel...
We consider the joint optimization of sensor placement and transmission structure for data gathering...
Abstract — This paper computes the sensing capacity of a sensor network, with sensors of limited ran...
This paper computes the sensing capacity of a sensor network, with sensors of limited range, sensing...
Abstract—We consider sensor networks that measure spatio-temporal correlated processes. An important...
We develop a framework for field estimation using wireless sensor networks, subject to network power...
Abstract—We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN) for...
We consider the joint optimization of sensor placement and transmission structure for data gathering...
© 2013 IEEE. This paper addresses the problem of selecting the most informative sensor locations out...
In this paper, we study the critical sensor density for partial connectivity of a large area sensor ...
International audienceAs sensors are energy constrained devices, one challenge in wireless sensor ne...
Abstract—Using large deviations results that characterize the amount of information per node on a tw...
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject t...
The detection of hidden two-dimensional Gauss-Markov random fields us-ing sensor networks is conside...
Abstract — The problem of maximizing detection performance subject to an energy constraint is analyz...
International audienceWe consider a sensor network which observes a spatially correlated random fiel...
We consider the joint optimization of sensor placement and transmission structure for data gathering...
Abstract — This paper computes the sensing capacity of a sensor network, with sensors of limited ran...
This paper computes the sensing capacity of a sensor network, with sensors of limited range, sensing...
Abstract—We consider sensor networks that measure spatio-temporal correlated processes. An important...
We develop a framework for field estimation using wireless sensor networks, subject to network power...
Abstract—We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN) for...
We consider the joint optimization of sensor placement and transmission structure for data gathering...
© 2013 IEEE. This paper addresses the problem of selecting the most informative sensor locations out...
In this paper, we study the critical sensor density for partial connectivity of a large area sensor ...
International audienceAs sensors are energy constrained devices, one challenge in wireless sensor ne...