In this paper, we present a model of distributed parameter estimation in networks, where agents have access to partially informative measurements over time. Each agent faces a loca...
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
This paper studies optimal input excitation design for parametric frequency response estimation. We will focus on least-squares estimation of Finite Impulse Response (FIR) models a...
Underwater acoustic localization usually relies on time of arrival (ToA) measurements, which are then converted into range estimates. However, the water medium is inhomogeneous and...
Christian R. Berger, Shengli Zhou, Peter Willett, ...
The detection and estimation of signals in noisy, limited data is a problem of interest to many scientific and engineering communities. We present a mathematically justifiable, com...