This paper provides an overview of recent developments in big data in the context of
biomedical and health informatics. It outlines the key characteristics of big data and how …

Wireless sensor networks produce a large amount of data that needs to be processed,
delivered, and assessed according to the application objectives. The way these data are …

An event-triggered mechanism is of great efficiency in reducing unnecessary sensor
samplings/transmissions and, thus, resource consumption such as sensor power and …

We deal with distributed estimation of deterministic vector parameters using ad hoc wireless
sensor networks (WSNs). We cast the decentralized estimation problem as the solution of …

This paper discusses nonparametric distributed learning. After reviewing the classical
learning model and highlighting the success of machine learning in centralized settings, the …

When choosing the technology options to develop a wireless sensor network (WSN), it is
vital that their performance levels can be assessed for the type of application intended. This …

Wireless sensor networks (WSNs) are highly resource constrained in terms of power supply,
memory capacity, communication bandwidth, and processor performance. Compression of …

In this research work, SnO2, NiO and SnO2/NiO nanocomposites were synthesized at low
temperature by modified sol–gel method using ultrasonication. Prepared samples were …

This paper reviews the classical decentralized decision theory in the light of new constraints
and requirements. The central theme that transcends various aspects of signal processing …

We consider the distributed estimation of an unknown vector signal in a resource
constrained sensor network with a fusion center. Due to power and bandwidth limitations …