Statistical Application of Wavelets

Catalog description

Credits 3. 3 Lecture Hours. Advanced wavelet-based algorithms designed for summarization of large and noisy data sets for subsequent statistical modeling and learning; theoretical component providing unified multiresolution-based framework for efficient modeling, synthesis, analysis, and processing of broad classes of signals and images; applications in geosciences, biomedical signal processing, signal and image denoising, medical diagnostics, financial data analysis. Prerequisite: Familiarity with computing in MATLAB, Octave, Python; STAT 627 or approval of instructor.