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Ryan Boyden edited subsubsection_Wavelet_Transform__.tex
over 8 years ago
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\subsubsection{Wavelet Transform}
The Wavelet Transform is an average value of the positive regions of a convolved image (Koch et al., 2015) (direct quote, is the citation ok?). We convolve the integrated intensity maps of our runs to Mexican Hat Kernals similar to section 3.2.4. We show the wavelet transforms at all computed scales in Figure 10. Koch et al. (2015) fits a portion of the transform to a power-law, based on the results of Gill & Henriksen (1990). We also produce power-law fits, that our runs appear to loosely follow. Run W2T2t0, our purely turbulent model, diverges tends to diverged from its fitted power-law behavior more than that of run W1T2t0.2, our turbulent model with feedback. We also note greater wavelet transform values in run W1T2t0.2 than in run W2T2t0.
(Eric, do you define the Mexican Hat Wavelet here differently than you define it in the Delta Variance section?)
