We explore fundamental performance limits of tracking a target in a two-dimensional field of
binary proximity sensors, and design algorithms that attain those limits. In particular, using …

The purpose of this study is to propose Context-Aware Support Vector Machine (C-SVM) for
application in a context-dependent recommendation system. It is important to consider users' …

This paper focuses on the development of a radio localization technique for a wireless
sensor network infrastructure where a large number of simple power-aware nodes are …

This paper presents two solutions for performing decentralised particle filtering in view of
non-linear, non-Gaussian tracking in sensor networks. The issue is that no known methods …

This paper considers the problem tracking a moving target in a multisensor environment
using distributed particle filters (DPFs). Particle filters have a great potential for solving …

This paper describes a technique for the probabilistic self-localization of a sensor network
based on noisy inter-sensor range data. Our method is based on a number of parallel …

This paper presents a novel distributed particle filter algorithm. To solve the problem of
fusing the output of multiple particle filters, a joint space over multiple realisations of the …

In this paper, we present the development of data and information processing algorithms for
target tracking in wireless sensor networks. Firstly, we propose a collaborative data and …

Transportation of data between nodes in a sensor network is expensive, as wireless radio
transmission depletes finite battery capacity. In addition, wireless data transmission is prone …

Estimating the positions of sensor nodes is a fundamental and crucial problem in ad hoc
wireless sensor networks (WSNs). In this paper, an accurate node localization method for …