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Let be an arbitrary stochastic sequence.
The phenomena of ROQ and missing measurements are governed by a Bernoulli distributed stochastic sequence.
Qiu and Yang [11] established another type strong limit theorem for stochastic sequence in 1999.
ξ ≈ 0 and ν ≈ 0 indicates stochastic sequence satisfies the normality requirement.
The randomly occurring nonlinearities are taken into account, which are governed by a Bernoulli distributed stochastic sequence.
A binary switching stochastic sequence with a known distribution is employed to describe the packet dropout phenomena.
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The stochastic sequences are thought as the observation symbols for the proposed GHMM.
Stochastic sequences ((mathcal {H}^{s}(n))_{ninmathbf {N}}) are analysed in Lemma 9, Section 5.3.
In recent years, some work has been done on the strong limit theorems for arbitrary stochastic sequences.
The purpose of this paper is to discuss further the strong limit theorems for arbitrary stochastic sequences.
By using Doob's [1] convergence theorem for martingale-difference sequence, we establish a class of new strong limit theorems for stochastic sequences.
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