Real and complex exponential data fitting is an important activity
in many different areas of science and engineering, ranging from
Nuclear Magnetic Resonance Spectroscopy and Lattice Quantum Chromodynamics
to Electrical and Chemical Engineering, Vision and Robotics. The
most commonly used norm in the approximation by linear combinations
of exponentials is the l2 norm (sum of squares of residuals), in
which case one obtains a nonlinear separable least squares problem.
A number of different methods have been proposed through the years
to solve these types of problems and new applications appear daily.
Necessary guidance is provided so that care should be taken when
applying standard or simplified methods to it. The described methods
take into account the separability between the linear and nonlinear
parameters, which have been quite successful. The accessibility
of good, publicly available software that has been very beneficial
in many different fields is also considered. This Ebook covers the
main solution methods (Variable Projections, Modified Prony) and
also emphasizes the applications to different fields. It is considered
essential reading for researchers and students in this field.