In this contribution, we implement a fully distributed diffusion field estimation algorithm based on the use of average consensus schemes. We show that the field reconstruction problem is equiva-lent to estimating the sources of the field, and then derive an exact inversion formula for jointly recovering these sources when they are localized and instantaneous. Next we adapt this formula to the sensor network setting when only spatiotemporal samples of the field are available, and only local interactions between the sensors are allowed. To this end, we propose a robust distributed algorithm for reconstructing two-dimensional diffusion fields, sampled with a network of arbitrarily placed sensors. The proposed distributed algorithm is validate...
This paper is concerned with the distributed field estimation problem using a sensor network, and th...
We consider a sensor network in which each sensor may take at every time iteration a noisy linear me...
Distributed implementations of the Expectation-Maximization (EM) algorithm reported in literature ha...
Sensor networks are becoming increasingly prevalent for monitoring physical phenomena of interest. F...
Sensor networks are becoming increasingly prevalent for monitoring physical phenomena of interest. F...
In this paper we consider a diffusion field induced by multi-ple point sources and address the probl...
In this paper we consider a diffusion field induced by multi-ple point sources and address the probl...
We consider diffusion fields induced by a finite number of spatially localized sources and address t...
Abstract—We consider the problem of reconstructing a dif-fusion field, such as temperature, from sam...
<p>We study a scalable approach to information fusion for large sensor networks. The algorithm, fiel...
We consider the problem of reconstructing a diffusion field, such as temperature, from samples colle...
<p>We study distributed estimation of dynamic random fields observed by a sparsely connected network...
Sensor networks have emerged as an important tool for the monitoring of physical fields of interest....
This paper considers an estimation network of many distributed sensors with a certain correlation st...
Consider a diffusion field induced by a finite number of lo-calized and instantaneous sources. In th...
This paper is concerned with the distributed field estimation problem using a sensor network, and th...
We consider a sensor network in which each sensor may take at every time iteration a noisy linear me...
Distributed implementations of the Expectation-Maximization (EM) algorithm reported in literature ha...
Sensor networks are becoming increasingly prevalent for monitoring physical phenomena of interest. F...
Sensor networks are becoming increasingly prevalent for monitoring physical phenomena of interest. F...
In this paper we consider a diffusion field induced by multi-ple point sources and address the probl...
In this paper we consider a diffusion field induced by multi-ple point sources and address the probl...
We consider diffusion fields induced by a finite number of spatially localized sources and address t...
Abstract—We consider the problem of reconstructing a dif-fusion field, such as temperature, from sam...
<p>We study a scalable approach to information fusion for large sensor networks. The algorithm, fiel...
We consider the problem of reconstructing a diffusion field, such as temperature, from samples colle...
<p>We study distributed estimation of dynamic random fields observed by a sparsely connected network...
Sensor networks have emerged as an important tool for the monitoring of physical fields of interest....
This paper considers an estimation network of many distributed sensors with a certain correlation st...
Consider a diffusion field induced by a finite number of lo-calized and instantaneous sources. In th...
This paper is concerned with the distributed field estimation problem using a sensor network, and th...
We consider a sensor network in which each sensor may take at every time iteration a noisy linear me...
Distributed implementations of the Expectation-Maximization (EM) algorithm reported in literature ha...