ABSTRACT
As we know, a (covariance) stationary process, X(t), is defined to be a process for which the following conditions hold:
1. E[X(t)] = μ (constant for all t). 2. Var[ i e a finite constant for all2X t t( )] ( . ., ).= <σ ∞ (12.1) 3. Cov[X(t), X(t + h)] = γ (h) (i.e., the covariance between random vari-
ables X(t) and X(t + h) depends only on h (and not on t)).
