Abstract
Wavelet transform theory includes a powerful and abstract set of signal processing tools. Students often understand the underlying mathematics of how to perform the procedures but lack the conceptual and computational understanding of how and when to apply wavelets to measured data. In this talk, we will discuss a project designed to take what is learned from textbooks and classroom lectures and apply these skills and tools to measured data from the field. The project is to cover an entire semester with multiple points for instructor evaluation and student revision. The end goal is that students will learn more signal processing skills through computational methods and data analysis and will produce a paper that can be part of a thesis/dissertation as well as a presentation at a future meeting.
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