• International Journal of Control, Automation, and Systems
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• 제6권2호
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• pp.269-277
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• 2008

This paper proposes a necessary and sufficient condition of convergence in the $L_2$-norm sense for a feedback-based iterative learning control (ILC) system including a multi-input multi-output (MIMO) linear time-invariant (LTI) plant. It is shown that the convergence conditions for a nominal plant and an uncertain plant are equal to the nominal performance condition and the robust performance condition in the feedback control theory, respectively. Moreover, no additional effort is required to design an iterative learning controller because the performance weighting matrix is used as an iterative learning controller. By proving that the least upper bound of the $L_2$-norm of the remaining tracking error is less than that of the initial tracking error, this paper shows that the iterative learning controller combined with the feedback controller is more effective to reduce the tracking error than only the feedback controller. The validity of the proposed method is verified through computer simulations.

• 대한수학회보
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• 제53권1호
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• pp.247-262
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• 2016

We propose and analyze spectral and pseudo-spectral Jacobi-Galerkin approaches for weakly singular Volterra integral equations (VIEs). We provide a rigorous error analysis for spectral and pseudo-spectral Jacobi-Galerkin methods, which show that the errors of the approximate solution decay exponentially in $L^{\infty}$ norm and weighted $L^2$-norm. The numerical examples are given to illustrate the theoretical results.

• East Asian mathematical journal
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• 제31권5호
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• pp.685-693
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• 2015

In this paper, we introduce fully discrete mixed discontinuous Galerkin approximations for parabolic problems. And we analyze the error estimates in $l^{\infty}(L^2)$ norm for the primary variable and the error estimates in the energy norm for the primary variable and the flux variable.

• 지구물리와물리탐사
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• 제8권2호
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• pp.170-176
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• 2005

속도중합의 역산을 이용하면 탄성파 자료처리에 있어서 다양한 처리가 가능하므로 이 분야는 최근에 들어 매우 유용한 영역으로 주목을 받고 있다. 하지만 다양한 처리에 적용하기 위해서는 사용되는 역산 방법이 잡음에 강하면서도 고해상도의 속도중합 결과를 만들 수 있어야 한다. 이러한 특성을 갖는 대표적인 역산에는 ${L_1}-norm$을 최소화시키는 IRLS(Iteratively Reweighted Least-Squares)방법을 주로 사용하였다. 본 논문에서는 이러한 성질을 갖는 또 다른 역산 방법의 하나로서 CGG (Conjugate Guided Gradient) 방법을 소개한다. CGG 방법은 반복적 최소자승법의 하나인 Conjugate Gradient (CG)방법을 변형시킨 형태로 ${L_1}-norm$을 최소화 시키는 역산법으로 활용할 수 있다. 본 논문에서는 CGG방법을 소개하고 기존의 IRLS방법과의 차이점 및 결과들을 비교하였다. 모의자료와 현장자료에 대한 실험결과를 통해서 CGG 방법이 IRLS방법과 마찬가지로 다양한 잔여/모델 norm을 최소화시키는 역산방법으로 사용될 수 있음을 보여준다.

• 전기전자학회논문지
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• 제20권2호
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• pp.136-142
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• 2016

본 논문에서는 혼합 norm을 이용한 가중치 함수 기반의 비국부 평균 노이즈 제거 방식을 제안한다. 비국부 평균 노이즈 제거 방식에서 중심 패치와 참조 패치의 오차에 대한 신뢰도는 노이즈 양 및 국부 활동성에 의존적인 특성을 갖고 있다. 본 논문에서는 혼합 norm 기반의 새로운 가중치 함수를 제안하고, 혼합 norm의 차수를 노이즈 정도 및 중심 패치의 국부 활동성에 의해 적응적으로 결정하여 비국부 평균 노이즈 제거 방식의 성능을 개선하고자 하였다. 실험 결과를 통해 기존의 비국부 평균 노이즈 제거 방식과 비교하여 제안 방식의 정량적 및 정성적 성능의 우수성을 확인할 수 있었다. 더불어, 제안 방식은 표준 유클리드 norm 기반의 다른 형태의 비국부 평균 노이즈 방식의 성능을 개선할 수 있는 능력이 있음을 확인할 수 있었다.

• 한국조경학회지
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• 제30권6호
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• pp.38-46
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• 2003

Perceived crowding is known as a necessary method to evaluate social carrying capacity in recreational settings. But according to the results of previous research, perceived crowding, use density, and satisfaction have shown weak and indirect correlations. The theory of visitors’ adjustment is one of several possible explanations for this poor relation. But the validity of the visitors’ adjustment theory has not been not inspected clearly. Therefore, the purposes of this study are to understand visitors’ adjustment theory and to examine visitors’ adjustment to the overuse of recreational settings. Study hypotheses were formulated through literature review and related to visitors’ adjustment in recreation density. Pour hypotheses were established and inspected with the case study, i.e., Rationalization : Visitors’ satisfaction isn't related to use density in recreation setting, 2) Product-shift : Preference norm is related to current use density, 3) Self-selection : Visitors’ satisfaction for the use level is generally high, and 4) Displacement : Norm interference is related to willingness to revisit. The case study was conducted during May and June,2001. According to the results of this survey, visitors adjust to overuse of recreation setting through rationalization and product shift (hypotheses l/2 acceptance). Current use density isn't related to visitors’ satisfaction and willingness to revisit (see table 3). And visitors’ preference norm is modified by situation (see table 4). Visitors’ satisfaction and willingness to revisit don't show a high correlation but moderately high (see table 5, hypothesis 3 acceptance). Differences between visitors’ preference norm and current use density is norm interference. Norm interference isn't related to willingness to revisit (see table 7). Therefore, the norm interference concept is not a useful method to explain visitors’ adjustment to the degree of overuse in a recreational setting (hypothesis 4 rejection). As for future directions, the following are proposed: 1) correctly understanding and reestablishing the visitor norm and norm interference concept, 2) introducing a composite research method to monitor visitors’ behavior and survey visitors’ attitudes and coping responses. These efforts would be helpful in the Planning and management of recreational settings to improve the quality of visitors’ experiences.

• 지구물리와물리탐사
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• 제19권4호
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• pp.220-227
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• 2016

해양 탄성파 탐사를 통해 취득한 자료에는 지하 매질에서 반사되어 오는 신호뿐만 아니라 해수면에서 되반사되어 발생하는 고스트가 존재한다. 고스트는 특정 주파수 성분을 약화시켜 탄성파 자료의 시간 해상도를 저하시킨다. 고스트를 효과적으로 제거하기 위해서는 정확한 고스트의 지연시간과 해수면의 반사계수가 요구된다. 고스트 지연시간은 해수면의 상하 움직임, 에어건과 스트리머의 움직임 및 벌림(offset) 거리 등에 의해 변하며, 해수면의 반사계수도 주파수, 평면파의 입사각 그리고 해상 상태에 따라 변한다. 이러한 영향을 고려한 고스트 지연시간을 추정하기 위하여 이 연구에서는 고스트 제거 트레이스 및 이의 자기상관 자료의 L-1 norm, L-2 norm 그리고 첨도(kurtosis)를 비교하였다. 자기상관자료의 L-1 norm을 계산하여 고스트 지연시간을 추정하는 것이 오차가 가장 적게 발생하였다. 현장자료의 파고를 고려하고 키르히호프 근사식을 이용하여 해수면의 반사계수를 계산하여 음원 및 수신기 고스트 제거에 적용하였다. 고스트를 제거함으로써 약화된 주파수 성분을 복원하였으며 시간 해상도가 향상된 구조보정 단면을 얻었다.

• ETRI Journal
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• 제36권1호
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• pp.42-50
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• 2014

Orthogonal frequency division multiplexing (OFDM) is a modulation technique that allows the transmission of high data rates over wideband radio channels subject to frequency selective fading by dividing the data into several narrowband and flat fading channels. OFDM has high spectral efficiency and channel robustness. However, a major drawback of OFDM is that the peak-to-average power ratio (PAPR) of the transmitted signals is high, which causes nonlinear distortion in the received data and reduces the efficiency of the high power amplifier in the transmitter. The most straightforward method to solve this problem is to use a nonlinear mapping algorithm to transform the signal into a new signal that has a smaller PAPR. One of the latest nonlinear methods proposed to reduce the PAPR is the $L_2$-by-3 algorithm, which is based on the discrete sliding norm transform. In this paper, a new algorithm based on the $L_2$-by-3 method is proposed. The proposed method is very simple and has a low complexity analysis. Simulation results show that the proposed method performs better, has better power spectral density, and is less sensitive to the modulation type and number of subcarriers than $L_2$-by-3.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1724-1731
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• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

• 대한수학회보
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• 제55권4호
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• pp.1209-1219
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• 2018

We provide a direct proof of the following theorem of Kalton, Hollenbeck, and Verbitsky [7]: let H be the Hilbert transform and let a, b be real constants. Then for 1 < p < ${\infty}$ the norm of the operator aI + bH from $L^p(\mathbb{R})$ to $L^p(\mathbb{R})$ is equal to $$\({\max_{x{\in}{\mathbb{R}}}}{\frac{{\mid}ax-b+(bx+a){\tan}{\frac{\pi}{2p}}{\mid}^p+{\mid}ax-b-(bx+a){\tan}{\frac{\pi}{2p}}{\mid}^p}{{\mid}x+{\tan}{\frac{\pi}{2p}}{\mid}^p+{\mid}x-{\tan}{\frac{\pi}{2p}}{\mid}^p}}\)^{\frac{1}{p}}$$. Our proof avoids passing through the analogous result for the conjugate function on the circle, as in [7], and is given directly on the line. We also provide new approximate extremals for aI + bH in the case p > 2.