EMD Performance Comparison: Single vs Double Floating Points
Dawid Laszuk, Oswaldo Cadenas, and Slawomir J. Nasuto
University of Reading, Reading, United Kingdom
Abstract—Empirical Mode Decomposition (EMD) is a data-driven method used to decompose data into oscillatory components. This paper examines to what extent the defined algorithm for EMD might be susceptible to data format. Two key issues with EMD are its stability and computational speed. This paper shows that for a given signal there is no significant difference between results obtained with single (binary32) and double (binary64) floating points precision. This implies that there is no benefit in increasing floating point precision when performing EMD on devices optimised for single floating point format, such as Graphical Processing Units (GPUs).
Index Terms—empirical mode decomposition, floating point arithmetic, intrinsic mode function, performance test, signal decomposition
Cite: Dawid Laszuk, Oswaldo Cadenas, and Slawomir J. Nasuto, "EMD Performance Comparison: Single vs Double Floating Points," International Journal of Signal Processing Systems, Vol. 4, No. 4, pp. 349-353, August 2016. doi: 10.18178/ijsps.4.4.349-353
Cite: Dawid Laszuk, Oswaldo Cadenas, and Slawomir J. Nasuto, "EMD Performance Comparison: Single vs Double Floating Points," International Journal of Signal Processing Systems, Vol. 4, No. 4, pp. 349-353, August 2016. doi: 10.18178/ijsps.4.4.349-353
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