Vasilisa Bashlovkina
ABSTRACT
This paper aims at developing a novel compression technique which breaks the "downward spiral" between compression ratio and recovery precision. Based on the previously developed Fuzzy Transform Compression (FTC), we design and implement a modified version of the algorithm, referred to as Fuzzy Compression Adaptive Transform (FuzzyCAT). The crux of FuzzyCAT is to adapt the transform parameters to the signal's curvature inferred from the time derivativesA comparative study with the Lightweight Temporal Compression (LTC) technique revealed that transmission costs of the FuzzyCAT nodes are much less than that of the LTC, which makes it an outstanding candidate for data compression in Wireless Sensor Networks.
- T. Schoellhammer and et al., "Lightweight Temporal Compression of Microclimate Datasets {Wireless Sensor Networks}," in Proc. of The 29th IEEE Int. Conf. on Local Computer Networks, pp. 516--524, 2004. Google Scholar
Digital Library
- I. Perfilieva, "Fuzzy Transforms," Transactions on Rough Sets II, pp. 63--81, 2004. Google ScholarDigital Library
Index Terms
- FuzzyCAT: a novel procedure for refining the F-transform based sensor data compression
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