Distributed compression-estimation using wireless sensor networks

350 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Consensus in Ad Hoc WSNs With Noisy Links—Part I: Distributed Estimation of Deterministic Signals (2008, background): “Fusion center (FC) based WSNs can perform decentralized estimation [17], but have limitations arising due to: i) the high transmission power required at each sensor to transmit its local information to the FC, that is proportional to the covered geographic area; and ii) lack of robustness in case of”
Distributed Event-Triggered Estimation Over Sensor Networks: A Survey (2020, background): “2) When an FC is absent, the sensor network itself is responsible for processing the raw collected data and is considered to be an ad-hoc sensor network; sensors have no hierarchy in the network and, thus, have the same type of processing and communication [21].”
Distributed Kalman filtering based on consensus strategies (2008, methodology): “Concerning estimation of dynamic processes we should mention the so called Sign of Innovation (SOI) Kalman filter [33], [17]; in this approach each sensor broadcasts to all sensors in the network the new information acquired by sensing the environment, so that each sensor solves a “centralized” (i.”