Measured bio and neuro responses, geophysical and socio-economic phenomena often possess intrinsic high frequency components and strong persistent serial correlations inhibiting statistical modeling by traditional techniques. In many modeling scenarios the low-frequency-trends are irrelevant and researchers focus on the high-frequency component and its low-dimensional descriptors. The talk overviews several traditional wavelet-based techniques for assessing the scaling in 1-, 2-, and 3-D data and some novel related techniques that are under ongoing research by the speaker and colleagues from Georgia Institute of Technology and Emory University. The focus will be on 2-D wavelet-based spectral tools. The applications include analysis and modeling of spectral responses in 1H NMR spectroscopy describing metabolic fluctuations in human plasma, classification of mammograms, turbulence, and assessment of doppler radar rainfall data.
Group for Research in Decision Analysis