Array Signal Processing in Wireless Sensor Networks

Distributed Signal Processing in Wireless Sensor Networks

Signal Processing in Wireless Sensor Networks

Distributed Signal Processing in Wireless Sensor Networks

6.1 The Problem of Distributed Detection and Data Fusion . . . . . . . . . . . . . . . . . . . . . . . . . .142 6.2 Fusion Architectures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .143 6.3 Recent Advances in Distributed Detection/Estimation in Resource-Constrained Wireless Sensor Networks . . . . . . . . . . . . ....

“Real” Signal Processing with Wireless Sensor Networks

This paper introduces some practical issues of the deployment of wireless sensor networks (WSNs) in closed loop digital signal processing (DSP) and control systems that require relatively fast, continuous data flow and real-time operation of the data collecting network, as in the case of traditional systems where sensors are attached by wire. The difficulties of the design of the wireless contr...

Efficient Signal Processing and Anomaly Detection in Wireless Sensor Networks

In this paper the node-level decision unit of a self-learning anomaly detection mechanism for office monitoring with wireless sensor nodes is presented. The node-level decision unit is based on Adaptive Resonance Theory (ART), which is a simple kind of neural networks. The Fuzzy ART neural network used in this work is an ART neural network that accepts analog inputs. A Fuzzy ART neural network ...