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A Learning-Theory Approach to Sensor Networks
October-December 2003 (vol. 2 no. 4)
pp. 44-49
Slobodan N. Simic, University of California, Berkeley

Supervised learning techniques have been applied in many diverse scenarios. They also might provide an effective approach to sensor network applications. A well-known learning-theory algorithm effectively applies to environmental monitoring, tracking of moving objects and plumes, and localization. This research, although preliminary, offers a beneficial perspective for the sensor network community to consider.

Index Terms:
supervised learning, random wireless sensor network, distributed algorithms
Citation:
Slobodan N. Simic, "A Learning-Theory Approach to Sensor Networks," IEEE Pervasive Computing, vol. 2, no. 4, pp. 44-49, Oct.-Dec. 2003, doi:10.1109/MPRV.2003.1251168
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