Working Paper Reconstruction of Boundary Sources through Sensor Observations

Regional Detection and Reconstruction of Unknown Internal or Boundary Sources

The purpose of this paper is to study the problem of regional detection, to characterize internal or boundary regionally detectable sources and regionally spy sensors, and to establish a relationship between these sensors and regionally strategic sensors. It is shown how to reconstruct a regionally detectable internal or a boundary source from a given output, with an extension to the case when ...

On the Determination of Point Sources by Boundary Observations: Uniqueness, Stability and Reconstruction

Reconstruction of Correlated Sources with Energy Harvesting Constraints

In this paper, we investigate how to minimize the distortion in the reconstruction of correlated sources. We consider a communication scenario where a sensor node is capable of harvesting energy from the environment and where the Fusion Center (FC), in order to exploit correlation, uses past observations as side information for decoding. We provide a convex formulation of the problem and derive...

A Geochemical Approach to the Palaeo Coastline Reconstruction in southern Khuzestan Plain

Several studies had been tried to illustrate the paleo coastlines of the Persian Gulf during the Holocene. A review of those researches reflects the fact that all of them have stablished their facts based on the sedimentary environment interpretations with no quantitative evidence. Generally, the study area is a changing environment which is a combination of riverine, continental, coastal and e...

Boundary Estimation for Multiply Digitized Objects Boundary Estimation for Multiply Digitized Objects

This paper considers the reconstruction of the boundary of a two-dimensional object from one or more digital representations that have been obtained by successive displacements of a digital image sensor. We explain how the reconstruction can be done for known displacements as well as for unknown random displacements that are uniformly distributed. In the latter case we assume that we can solve ...