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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Coates, M. Psaromiligkos, I. |
| Copyright Year | 2004 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, Que., Canada (Coates, M.; Psaromiligkos, I.) |
| Abstract | Sensor networks have exciting potential applications in agriculture and medicine, where after the application of treatment, it is beneficial not merely to track the response but to assess the causal impact of the treatment reception. We describe a distributed algorithm for the evaluation of the average causal effect of treatment reception upon response. Our procedure applies the expectation-maximization algorithm across a graphical model of the system, using local message-passing techniques. The key collaborative step in the algorithm is simple message aggregation and averaging, which we perform over a tree network topology. Finally, for completeness purposes, we describe a simple framework for the construction and maintenance of the tree topology that provides a robust mechanism for executing the algorithm using spread-spectrum or ultra-wideband communication. |
| File Size | 247733 |
| File Format | |
| ISBN | 0780384849 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2004.1326692 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2004-05-17 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wireless sensor networks Medical treatment Tree graphs Network topology Agriculture Distributed algorithms Expectation-maximization algorithms Graphical models Collaboration Robustness |
| Content Type | Text |
| Resource Type | Article |
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