A knowledge of linear systems provides a firm foundation for the study
of optimal control theory and many areas of system theory and signal
processing. State-space techniques developed since the early sixties
have been proved to be very effective. The main objective of this book
is to present a brief and somewhat complete investigation on the theory
of linear systems, with emphasis on these techniques, in both
continuous-time and discrete-time settings, and to demonstrate an
application to the study of elementary (linear and nonlinear) optimal
control theory. An essential feature of the state-space approach is that
both time-varying and time-invariant systems are treated systematically.
When time-varying systems are considered, another important subject that
depends very much on the state-space formulation is perhaps real-time
filtering, prediction, and smoothing via the Kalman filter. This subject
is treated in our monograph entitled "Kalman Filtering with Real-Time
Applications" published in this Springer Series in Information Sciences
(Volume 17). For time-invariant systems, the recent frequency domain
approaches using the techniques of Adamjan, Arov, and Krein (also known
as AAK), balanced realization, and oo H theory via Nevanlinna-Pick
interpolation seem very promising, and this will be studied in our
forthcoming monograph entitled "Mathematical Ap- proach to Signal
Processing and System Theory". The present elementary treatise on linear
system theory should provide enough engineering and mathe- of these two
subjects.