Now showing items 1-5 of 5
Optimal Sampling Strategies for Multiscale Stochastic Processes
In this paper, we determine which non-random sampling of fixed size gives the best linear predictor of the sum of a finite spatial population. We employ different multiscale superpopulation models and use the minimum ...
Broadcast Detection Structures with Applications to Sensor NetworksDistributed Structures, Sequential Optimization, and Quantization for Detection
Data broadcasting is potentially an effective and efficient way to share information in wireless sensor networks. Broadcasts offer energy savings over multiple, directed transmissions, and they provide a vehicle to exploit ...
Universal Distributed Sensing via Random Projections
This paper develops a new framework for distributed coding and compression in sensor networks based on distributed compressed sensing (DCS). DCS exploits both intra-signal and inter-signal correlations through the concept ...
Robust Distributed Estimation Using the Embedded Subgraphs Algorithm
We propose a new iterative, distributed approach for linear minimum mean-square-error (LMMSE) estimation in graphical models with cycles. The embedded subgraphs algorithm (ESA) decomposes a loopy graphical model into a ...
An Architecture for Distributed Wavelet Analysis and Processing in Sensor Networks
Distributed wavelet processing within sensor networks holds promise for reducing communication energy and wireless bandwidth usage at sensor nodes. Local collaboration among nodes de-correlates measurements, yielding a ...