• Communications for Statistical Applications and Methods
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• 제24권4호
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• pp.367-382
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• 2017

We consider an infinite-order long-memory heterogeneous autoregressive (HAR) model, which is motivated by a long-memory property of realized volatilities (RVs), as an extension of the finite order HAR-RV model. We develop bootstrap tests for structural mean or variance changes in the infinite-order HAR model via stationary bootstrapping. A functional central limit theorem is proved for stationary bootstrap sample, which enables us to develop stationary bootstrap cumulative sum (CUSUM) tests: a bootstrap test for mean break and a bootstrap test for variance break. Consistencies of the bootstrap null distributions of the CUSUM tests are proved. Consistencies of the bootstrap CUSUM tests are also proved under alternative hypotheses of mean or variance changes. A Monte-Carlo simulation shows that stationary bootstrapping improves the sizes of existing tests.

• 대한수학회보
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• 제54권3호
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• pp.895-909
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• 2017

This paper is concerned with the following fourth-order elliptic equations $${\Delta}^2u-{\Delta}u+V(x)u-{\frac{k}{2}}{\Delta}(u^2)u=f(x,u),\text{ in }{\mathbb{R}}^N$$, where $N{\leq}6$, ${\kappa}{\geq}0$. Under some appropriate assumptions on V(x) and f(x, u), we prove the existence of infinitely many negative-energy solutions for the above system via the genus properties in critical point theory. Some recent results from the literature are extended.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.174-178
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• 2002

This paper discusses a blind equalization technique for FIR channel system, that might be minimum phase or not, in digital communication. The proposed techniques consist of two parts. One is to estimate the original channel coefficients based on fourth-order cumulants of the channel output, the other is to employ RBF neural network to model an inverse system fur the original channel. Here, the estimated channel is used as a reference system to train the RBF. The proposed RBF equalizer provides fast and easy teaming, due to the structural efficiency and excellent recognition-capability of R3F neural network. Throughout the simulation studies, it was found that the proposed blind RBF equalizer performed favorably better than the blind MLP equalizer, while requiring the relatively smaller computation steps in tranining.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1361-1369
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• 2008

The analysis of software reliability model provides the means to analysts, software engineers, and systems analysts and developers who want to predict, estimate, and measure failure rate of occurrences in software. In this paper, reliability growth model, in which the operating time between successive failure is a continuous random variable, is proposed. This model is based on order statistics of two parameters Burr type XII distribution. We propose the measure based on U-plot. Also the performance of the suggested model is tested on real data set.

• Journal of the Korean Statistical Society
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• 제32권3호
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• pp.271-288
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• 2003

In this paper, when the variance of the normal distribution is related to the mean, we develop noninformative priors such as matching priors and reference priors. We prove that the second order matching prior matches alternative coverage probabilities up to the same order and also it is a HPD matching prior. It turns out that one-at-a-time reference prior satisfies a second order matching criterion. Then using these noninformative priors, we develop a Bayesian test procedure for the equality of the means and variances of two independent normal distributions using fractional Bayes factor. Some simulation study is performed, and a real data example is also provided.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.1044-1049
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• 2001

Classical deconvolution methods for source identification following linear filtering can only be used if the transfer function of the system is known. For many practical situations, however, this information is not accessible and/or is time varying. The problem addressed here is that of reconstruction of the original input from only the measured signal. This is known as 'blind deconvolution'. By using Higher Order Statistics (HOS), the restoration of the input signal is established through the maximisation of higher order moments (cumulants) with respect to the characteristics of the signals concerned. This restoration is achieved by constructing an inverse filter considering the choice of the initial inverse filter type. As a practical application, an experimental verification is carried out for the restoration of our impacting signal arising in the response of a cantilever beam with an end stop when randomly excited.

• 대한수학회보
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• 제61권3호
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• pp.745-762
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• 2024

In this paper, we study the existence of finite order meromorphic solutions of the following non-linear difference equation fⁿ(z) + P_d(z, f) = p₁e^α1z + p₂e^α2z + p₃e^α3z, where n ≥ 2 is an integer, P_d(z, f) is a difference polynomial in f of degree d ≤ n - 2 with small functions of f as its coefficients, p_j (j = 1, 2, 3) are small meromorphic functions of f and α_j (j = 1, 2, 3) are three distinct non-zero constants. We give the expressions of finite order meromorphic solutions of the above equation under some restrictions on α_j (j = 1, 2, 3). Some examples are given to illustrate the accuracy of the conditions.

• 응용통계연구
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• 제24권5호
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• pp.963-977
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• 2011

다변량 자료를 분석함에 있어 자료의 차원을 축소하는데 활용되는 중요한 툴 중 하나인 PCA 분석(주성분 분석, Principal Component Analysis)을 실시간으로 처리해야 하는 적용 분야가 최근 늘고 있다. PCA 분석에서는 표본 공분산 행렬의 고유값과 고유벡터를 도출하는 것이 관건인데, 자료의 양이 방대하며 고차원인 경우 이를 실시간으로 수행하기에는 어려움이 따른다. 이러한 문제점을 해결하기 위해서 Erdogmus 등 (2004)는 일차 섭동 이론(first order perturbation theory)을 활용하여 공분산 행렬의 고유값과 고유벡터를 추정하는 Recursive PCA 방법을 제안했다. 이 방법은 추가된 자료의 양이 많지 않은 경우는 상당히 정확하지만, 추가된 자료의 양이 많아짐에 따라 오차도 커진다는 한계를 가지고 있다. 본 논문은 공분산 행렬의 고유값과 고유벡터가 가지고 있는 수학적 관계를 이용하여 Erdogmus 등 (2004)가 제안한 Recursive PCA 방법을 수정한 Modi ed Recursive PCA 방법을 제안하다. 또한, 모의 실험을 통해 Recursive PCA 방법과 Modi ed Recursive PCA 방법에서의 고유값과 고유벡터 추정값의 정확도를 비교해 보았으며 그 결과 기존 Recursive PCA 방법 보다 정확한 추정이 가능함을 확인할 수 있었다.

• Journal of Electrical Engineering and Technology
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• 제7권5호
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• pp.797-806
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• 2012

Fault detection and isolation (FDI) algorithms provide fault monitoring methods in GPS measurement to isolate abnormal signals from the GPS satellites or the acquired signal in receiver. In order to monitor the occurred faults, FDI generates test statistics and decides the case that is beyond a designed threshold as a fault. For such problem of fault detection and isolation, this paper presents and evaluates position domain integrity monitoring methods by formulating various pseudorange prediction methods and investigating the resulting test statistics. In particular, precise measurements like carrier phase and Doppler rate are employed under the assumption of fault free carrier signal. The presented position domain algorithm contains the following process; first a common pseudorange prediction formula is defined with the proposed variations in pseudorange differential update. Next, a threshold computation is proposed with the test statistics distribution considering the elevation angle. Then, by examining the test statistics, fault detection and isolation is done for each satellite channel. To verify the performance, simulations using the presented fault detection methods are done for an ideal and real fault case, respectively.

• Journal of the Korean Data and Information Science Society
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• 제25권4호
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• pp.869-880
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• 2014

본 연구에서는 향후 H/W 교과과정에서 효과적인 확률 및 통계 교육 방안을 제시하기 위한 목적으로, 첫째 H/W 교과과정에서 전공 선수교과목으로서 확률 및 통계 교과목의 필요성 인식을 전공교과목과의 관련성을 통해 파악하였다. 둘째, 확률 및 통계와 관련된 H/W 전공교과목들은 연계하여 교수-학습을 병행하면 H/W 전공교과목에 대한 이해도를 향상시킬 수 있으므로, 실제 교육현장 적용을 통해 확률 및 통계를 연계한 H/W 교과목의 연구 및 개발과 그에 따른 교육효과를 분석하였다. 또한 본 연구에서는 설문조사와 교육사례를 실시하여 통계적으로 분석하고 H/W 교과과정에서 확률 및 통계의 연계성을 통한 바람직한 교육의 한 방법을 제시하였다.