Model reduction is an important engineering problem in which one aims to
replace an elaborate model by a simpler model without undue loss of
accuracy. The accuracy can be mathematically measured in several
possible norms and the Hankel norm is one such. The Hankel norm gives a
meaningful notion of distance between two linear systems: roughly
speaking, it is the induced norm of the operator that maps past inputs
to future outputs. It turns out that the engineering problem of model
reduction in the Hankel norm is closely related to the mathematical
problem of finding solutions to the sub-optimal Nehari-Takagi problem,
which is called "the sub-optimal Hankel norm approximation problem" in
this book. Although the existence of a solution to the sub-optimal
Hankel norm approximation problem has been known since the 1970's, this
book presents explicit solutions and, in particular, new formulae for
several large classes of infinite-dimensional systems for the first
time.