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INFORMATION AND INFORMATION STABILITY
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absolutely continuous according arbitrary average conditional information Chapter Comparing completely regular complex-valued random conditional entropy converges COROLLARY defined definition denote different from zero discrete-parameter processes EeSx Ei(t EI(tj entropy density entropy rate entropy stability equation ergodic everywhere dense exists family of pairs family of random finite variance follows forms a Markov formula gaussian random variables i(Tj implies inequality information density information rate information stability integer joint spectral densities joint spectral functions Lemma Markov chain measurable function measurable spaces multi-dimensional mutually independent non-generalized non-singular normal distribution obtain parameter partition perpendiculars process tj proof proper values proper vectors properties proves random variable consisting random variable tj rank of regularity relations Remark result right side Section singular with respect spectral and joint stationary and stationarily stationary gaussian process stationary process stationary random processes sufficiently large supremum T-oo theorem wide-sense stationary