• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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• pp.49-52
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• 1999

A subspace-based identification method of the Wiener model, consisting of a state-space linear block and a polynomial static nonlinearity at the output, is used to retrieve from discrete sample data the accurate information about the nonlinear dynamics. Wiener model may be incorporated into model predictive control (MPC) schemes in a unique way which effectively removes the nonlinearity from the control problem, preserving many of the favorable properties of linear MPC. The control performance is evaluated with simulation studies where the original first-principles model for a continuous MMA polymerization reactor is used as the true process while the identified Wiener model is used for the control purpose. On the basis of the simulation results, it is demonstrated that, despite the existence of unmeasured disturbance, the controller performed quite satisfactorily for the control of polymer qualities with constraints.

• 대한수학회지
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• 제38권2호
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• pp.311-319
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• 2001

We show that it is possible to associate diffusion processes to second order perturbations of the Ornstein-Uhlenbeck operator L on the Wiener space of the form L = L + 1/2∑L$^2$(sub)ξ(sub)$\kappa$ where the ξ(sub)$\kappa$ are "tangent processes" (i.e., semimartingales with antisymmetric diffusion coefficients).

• Journal of applied mathematics & informatics
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• 제34권1_2호
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• pp.167-178
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• 2016

In this paper, we study the stochastic integral of processes taking values of generalized operators based on a triple E ⊂ H ⊂ E^∗, where H is a Hilbert space, E is a countable Hilbert space and E^∗ is the strong dual space of E. For our purpose, we study E-valued Wiener processes and then introduce the stochastic integral of L(E, F^∗)-valued process with respect to an E-valued Wiener process, where F^∗ is the strong dual space of another countable Hilbert space F.

• 충청수학회지
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• 제5권1호
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• pp.23-34
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• 1992

This is an extension of results of Wiener's nonlinear noise theory from noises generated by the Wiener process to noises generated by processes with stationary Gaussian increments. In particular, using Nisio's Approach, we show that every measurable ergodic noise can be approximated in law by Gaussian process-presentable noise.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.501-506
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• 1998

A mathematical model is developed to describe the relationship between the manipulated variables (e.g. jacket inlet temperature and feed flow rate) and the important qualities (e.g conversion and weight average molecular weight (Mw)) in a continuous polymerization reactor. The subspace-based identification method for Wiener model is used to retrieve from the discrete sample data the accurate information about both the structure and initial parameter estimates for iterative parameter optimization methods. The comparison of the output of the identified Wiener model with the outputs of a non-linear plant model shows a fairly satisfactory degree of accordance.

• Journal of the Korean Statistical Society
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• 제26권1호
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• pp.57-74
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• 1997

Csorgo-Revesz type theorems for Wiener process are developed to those for Gaussian process. In particular, some results of superior and inferior limits for the increments of a Gaussian process are differently obtained under mild conditions, via estimating probability inequalities on the suprema of a Gaussian process.

• 대한수학회지
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• 제33권4호
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• pp.813-822
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• 1996

Let ${W(t); 0 \leq t < \infty}$ be a standard Wiener process on a probability space $(\Omega, \Im , P)$.

• 충청수학회지
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• 제12권1호
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• pp.133-146
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• 1999

Let {X(t), $t{\geq}0$} be a stochastic integral process represented by stable random measure or multiple Ito-Wiener integrals. Under some conditions, we prove the continuity and self-similarity of these stochastic integral processes. As an application, we get Gaussian chaos which has some shift continuous function.

• Korean Chemical Engineering Research
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• 제61권1호
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• pp.89-96
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• 2023

동적 선형 블록과 정적 비선형 블록이 직렬로 연결되어 있는 Wiener형 비선형 모델은 여러 화학 공정의 동특성을 묘사하는데 널리 사용되는데, Wiener형 비선형 공정의 모델 확인은 다소 긴 공정 활성화 데이터가 필요하다. 본 연구는 이러한 단점을 보완하기 위하여 단일 계단 응답으로부터 Wiener형 비선형 공정 모델을 찾아낼 수 있는 새로운 모델 확인 방법을 제안한다. 제안된 방법은 계단 응답의 초기 응답으로부터 선형 동적 블록의 예측 응답을 얻어 선형 동적 블록의 모델을 확인하고, 이어서 비선형 정적 블록의 모델을 확인한다. 본 방법은 단일 계단 응답만을 사용하여 공정 모델 확인을 위해 필요한 공정 응답을 얻는 과정에서 시간과 비용적으로 큰 이득을 얻을 수 있다. 제안된 공정 확인 방법의 성능은 대표적인 Wiener형 비선형 공정인 pH 적정 공정과 액위 공정을 대상으로 검증되었다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2002년도 춘계 학술발표회 논문집
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• pp.55-60
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• 2002

We present an extension of the Wong-Zakai type approximation theorem for a multiple stochastic integral. Using a piecewise linear approximation $W^{(n)}$ of a Wiener process W, we prove that the multiple integral processes {${\int}_{0}^{t}{\cdots}{\int}_{0}^{t}f(t_{1},{\cdots},t_{m})W^{(n)}(t_{1}){\cdots}W^{(n)}(t_{m}),t{\in}[0,T]$} where f is a given symmetric function in the space $C([0,T]^{m})$, converge to the multiple Stratonovich integral of f in the uniform $L^{2}$-sense.