Name
Abstract | ||
|---|---|---|
The computational and memory resources of wireless sensor nodes are typically very limited, as the employed low-energy microcontrollers provide only hardware support for 16 bit integer operations and have very limited random access memory (RAM). These limitations prevent the application of modern signal processing techniques to pre-process the collected sensor data for energy and bandwidth efficie... |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/SURV.2011.100110.00059 | IEEE Communications Surveys & Tutorials |
Keywords | Field | DocType |
Wavelet transforms,Random access memory,Tutorials,Approximation methods,Image coding,Microcontrollers | Lifting scheme,Computer science,Discrete wavelet transform,Artificial intelligence,Computer engineering,Wavelet packet decomposition,Wavelet,Wavelet transform,Distributed computing,Computer vision,Second-generation wavelet transform,Cascade algorithm,Wireless sensor network | Journal |
Volume | Issue | Citations |
13 | 2 | 19 |
PageRank | References | Authors |
1.10 | 24 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephan Rein | 1 | 83 | 7.48 |
| Martin Reisslein | 2 | 1661 | 114.91 |