Discrete Stochastic Processes and Optimal Filtering

A discrete time process is a family of r.v.
where T called the time base is a countable set of instants. X t j is the r.v. of the family considered at the instant t j.
Ordinarily, the t j are uniformly spread and distant from a unit of time and in the sequence T will be equal to
and the processes will be still denoted X T or, if we wish to be precise,
.
In order to be able to study correctly some sets of r.v. X j of X T and not only the r.v. X j individually, it is in our interests to consider the latter as being definite mappings on the same set and this leads us to an exact definition.
DEFINITION. Any X T family with measurable mappings is called a real discrete time stochastic process:
We also say that the process is defined on the fundamental space ( ?, a).
In general a process X T is associated with a real phenomenon, that is to say that the X j represent (random) physical, biological, etc. values. For example the intensity of electromagnetic noise coming from a certain star.
For a given ?, that is to say after the phenomenon has been performed, we obtain the values x j = X j ( ?).
DEFINITION. x T = { x j