Complete moment convergence for the widely orthant dependent linear processes with random coefficients

2020 ◽  
pp. 1-15 ◽  
Author(s):  
Dawei Lu ◽  
Lina Wang
Keyword(s):  
Random Coefficients ◽  
Complete Moment Convergence ◽  
Linear Processes ◽  
Moment Convergence ◽  
Widely Orthant Dependent

Complete moment convergence for the dependent linear processes with application to the state observers of linear-time-invariant systems

2020 ◽  
Vol 65 (4) ◽  
pp. 725-745
Author(s):  
Chao Lu ◽  
Chao Lu ◽  
Xuejun J Wang ◽  
Xuejun J Wang ◽  
Yi Wu ◽  
...  
Keyword(s):  
Linear Time ◽  
The State ◽  
Complete Moment Convergence ◽  
Linear Processes ◽  
Linear Time Invariant ◽  
Moment Convergence ◽  
State Observers ◽  
Linear Time Invariant Systems ◽  
Time Invariant

Пусть $X_t=\sum_{j=-\infty}^{\infty}A_j\varepsilon_{t-j}$ - зависимый линейный процесс, где $\{\varepsilon_n, n\in \mathbf{Z}\}$ - последовательность $m$-обобщенных отрицательно зависимых ($m$-END) случайных величин с нулевым средним, которая стохастически доминируется случайной величиной $\varepsilon$, и пусть $\{A_n, n\in \mathbf{Z}\}$ - другая последовательность случайных величин с нулевым средним, обладающая свойством $m$-END. При подходящих условиях установлена полная моментная сходимость для зависимых линейных процессов. В частности, приведены достаточные условия полной моментной сходимости. В качестве приложения исследуется сходимость наблюдателей состояния для линейных стационарных систем.

scholarly journals Complete moment convergence of moving average processes for m-WOD sequence

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Lihong Guan ◽  
Yushan Xiao ◽  
Yanan Zhao
Keyword(s):  
Moving Average ◽  
Random Variables ◽  
Random Variable ◽  
Complete Moment Convergence ◽  
Real Numbers ◽  
Mild Conditions ◽  
Moment Convergence ◽  
Summable Sequence ◽  
Moving Average Processes ◽  
Widely Orthant Dependent

AbstractIn this paper, the complete moment convergence for the partial sum of moving average processes $\{X_{n}=\sum_{i=-\infty }^{\infty }a_{i}Y_{i+n},n\geq 1\}$ { X n = ∑ i = − ∞ ∞ a i Y i + n , n ≥ 1 } is established under some mild conditions, where $\{Y_{i},-\infty < i<\infty \}$ { Y i , − ∞ < i < ∞ } is a sequence of m-widely orthant dependent (m-WOD, for short) random variables which is stochastically dominated by a random variable Y, and $\{a_{i},-\infty < i<\infty \}$ { a i , − ∞ < i < ∞ } is an absolutely summable sequence of real numbers. These conclusions promote and improve the corresponding results from m-extended negatively dependent (m-END, for short) sequences to m-WOD sequences.

scholarly journals Convergence Theorems for m -Coordinatewise Negatively Associated Random Vectors in Hilbert Spaces

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Lyurong Shi
Keyword(s):  
Hilbert Spaces ◽  
Law Of Large Numbers ◽  
Linear Process ◽  
Random Coefficients ◽  
Complete Moment Convergence ◽  
Random Vectors ◽  
Strong Law ◽  
Negatively Associated ◽  
Moment Convergence ◽  
Large Numbers

In this study, some new results on convergence properties for m -coordinatewise negatively associated random vectors in Hilbert space are investigated. The weak law of large numbers, strong law of large numbers, complete convergence, and complete moment convergence for linear process of H-valued m -coordinatewise negatively associated random vectors with random coefficients are established. These results improve and generalise some corresponding ones in the literature.

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