Effectively Interpreting Discrete Wavelet Transformed Signals [Lecture Notes]

Following two decades of research focusing on the discrete wavelet transform (DWT) and driven by students' high level of questioning, I decided to write this essay on one of the most significant tools for time-frequency signal analysis. As it is widely applicable in a variety of fields, I invite readers to follow this lecture note, which is specially dedicated to show a practical strategy for the interpretation of DWT-based transformed signals while extracting useful information from them. The particular focus resides on the procedure used to find the time support of frequencies and how it is influenced by the wavelet family and the support size of corresponding filters.