A central goal in signal analysis is to extract information from signals that are
related to real-world phenomena. Examples are the analysis of speech, images,
and signals in medical or geophysical applications. One reason for analyzing
such signals is to achieve better understanding of the underlying physical
phenomena. Another is to find compact representations of signals which
allow compact storage or efficient transmission of signals through real-world
environments. The methods of analyzing signals are wide spread and range
from classical Fourier analysis to various types of linear time-frequency trans-
transforms and model-based and non-linear approaches. This book concentrates on
transforms, but also gives a brief introduction to linear estimation theory and
related signal analysis methods. The text is self-contained for readers with
some background in system theory and digital signal processing, as typically
gained in undergraduate courses in electrical and computer engineering.