The theory of random functions is a very important and advanced part of
modem probability theory, which is very interesting from the
mathematical point of view and has many practical applications. In
applications, one has to deal particularly often with the special case
of stationary random functions. Such functions naturally arise when one
considers a series of observations x(t) which depend on the real-valued
or integer-valued ar- gument t ("time") and do not undergo any
systematic changes, but only fluctuate in a disordered manner about some
constant mean level. Such a time series x(t) must naturally be described
statistically, and in that case the stationary random function is the
most appropriate statistical model. Stationary time series constantly
occur in nearly all the areas of modem technology (in particular, in
electrical and radio engineering, electronics, and automatic control) as
well as in all the physical and geophysical sciences, in many other ap-
mechanics, economics, biology and medicine, and also plied fields. One
of the important trends in the recent development of science and
engineering is the ever-increasing role of the fluctuation phenomena
associated with the stationary disordered time series. Moreover, at
present, more general classes of random functions related to a class of
stationary random functions have also been appearing quite often in
various applied studies and hence have acquired great practical
importance.