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SENSYS
2006
ACM
13 years 10 months ago
Capturing high-frequency phenomena using a bandwidth-limited sensor network
Small-form-factor, low-power wireless sensors—motes—are convenient to deploy, but lack the bandwidth to capture and transmit raw high-frequency data, such as human voices or n...
Ben Greenstein, Christopher Mar, Alex Pesterev, Sh...
ACL
2012
11 years 7 months ago
Improving Word Representations via Global Context and Multiple Word Prototypes
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
IPSN
2009
Springer
13 years 11 months ago
Near-optimal Bayesian localization via incoherence and sparsity
This paper exploits recent developments in sparse approximation and compressive sensing to efficiently perform localization in a sensor network. We introduce a Bayesian framework...
Volkan Cevher, Petros Boufounos, Richard G. Barani...
GLOBECOM
2009
IEEE
13 years 8 months ago
Compressed Sensing Reception of Bursty UWB Impulse Radio is Robust to Narrow-Band Interference
—We have recently proposed a novel receiver for Ultra-Wide-band Impulse-Radio communication in bursty applications like Wireless Sensor Networks. The receiver, based on the princ...
Anand Oka, Lutz H.-J. Lampe
EVOW
2009
Springer
13 years 8 months ago
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 uni...
Markus Wälchli, Torsten Braun