• 전자공학회논문지B
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• 제29B권3호
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• pp.16-24
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• 1992

In this paper, we solve the problem of designing a robust optimal controller which minimizes the H$\infty$-norm of the mixed sensitivity function matrix for linear multivariable systems. For a given minimized value, ${\gamma}$>o, an algorithm of finding all stabilizing controllers, such that the H$\infty$-norm of the mixed sensitivity function matrix is less than ${\gamma}$, is developed. The proposed algorithm, which is based on the model-matching and the interpolation theory, can be used for the H$\infty$-optimization problem.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제25권3호
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• pp.107-116
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• 2021

We introduce optimization algorithms using Bregman Divergence for solving non-negative matrix factorization (NMF) problems. Bregman divergence is known a generalization of some divergences such as Frobenius norm and KL divergence and etc. Some algorithms can be applicable to not only NMF with Frobenius norm but also NMF with more general Bregman divergence. Matrix Factorization is a popular non-convex optimization problem, for which alternating minimization schemes are mostly used. We develop the Bregman proximal gradient method applicable for all NMF formulated in any Bregman divergences. In the derivation of NMF algorithm for Bregman divergence, we need to use majorization/minimization(MM) for a proper auxiliary function. We present algorithmic aspects of NMF for Bregman divergence by using MM of auxiliary function.

• Korean Journal of Mathematics
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• 제31권3호
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• pp.305-311
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• 2023

We exhibit some properties of the weighted Berezin transform T_αf on L^∞(B_n) and on L¹(B_n). As the main result, we prove that if f ∈ L^∞(B_n) with lim_k→∞ T^k_αf exists, then there exist unique M-harmonic function g and $h{\in}{\bar{(I-T_{\alpha})L^{\infty}(B_n)}}$ such that f = g + h. We also show that of the norm of weighted Berezin operator T_α on L¹(B_n, ν) converges to 1 as α tends to infinity, where ν is an ordinary Lebesgue measure.

• 대한물리의학회지
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• 제13권2호
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• pp.61-68
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• 2018

PURPOSE: This study aimed to examine the effects of self-stretching (SS) and joint mobilization (JM) on pain, craniovertebral angle (CVA), autonomic system function in chronic cervical pain patient with forward head posture (FHP). METHODS: A total of 30 male college students were selected as study subjects, and were divided into Group I (general physical therapy; GPT, n=10), Group II (GPT+SS, n=10), Group III (GPT+JM, n=10). All groups were evaluated three times a week for 4 weeks. Pain was measured by visual analogue scale (VAS), CVA was measured using digital goniometer and autonomic system function (heart rate; HR, skin conductivity; SC, LF norm, HF norm, LF/HF ratio) was measured by Biofeedback ProComp Infiniti. After 4 weeks, paired t-test was used to compare the changes within the group and one way ANOVA was used to compare those between the groups. RESULTS: In Group I, VAS was significantly decreased. In Group II and III was a significantly change in all items. In comparison between Group I and II was a difference in all items except HR. In comparison between Group I and III was a difference in all items. In comparison between Group II and III was a difference in VAS, LF norm and LF/HF ratio. CONCLUSION: This study showed that SS and JM can effectively reduce pain and normalize the autonomic system function.

• 한국정밀공학회지
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• 제27권12호
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• pp.59-66
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• 2010

We developed a model-based controller for 6-DOF micropositioning of a precision stage using $H_{\infty}$ norm, For the design, a state-space system of the mathematical model of the stage is derived In developing the controller, weighting functions are effectively designed in consideration of upper bounds of the sensitivity of the control loop and control input. Step responses in open and closed loop control are provided to verify the micropositioning performance of the stage. By applying the developed controller we prove that the inverse of the weighting function forms the upper bound of the control loop. It is also found that the controller makes the same sensitivity shape with all the DOFs due to the use of $H_{\infty}$ norm. The developed controller is expected to be applied successfully for industrial use.

• 한국정보통신학회논문지
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• 제11권10호
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• pp.1828-1834
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• 2007

본 논문에서는 웨이블릿 변환을 기반으로 한 새로운 컬러영상 워터마킹 기법을 제안한다. 먼저 RGB컬러영역을 YCbCr 좌표계로 변환한다. 그리고 워터마크에 대해 Arnold 변환을 하여 워터마크의 상관성을 적게 만든다. 그 후, 선형비트확장 기법을 적용하여 확대된 워터마크를 웨이블릿 변환된 컬러 영상의 Y 영역-저주파대에 일정한 강도로 삽입한다. 워터마크를 추출할 때는 F-노름(norm) 함수를 이용한다. 다양한 칼라영상에 대해 실험을 한 결과 제안한 방법은 충실도와 강인성 측면에서 우수한 특성을 가짐을 확인하였다.

• 대한수학회지
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• 제45권6호
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• pp.1561-1576
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• 2008

In this paper we shall prove some weighted norm inequalities of the form $${\int}_{R^n}\;|Tf(x)|^pu(x)dx\;{\leq}\;C_p\;{\int}_{R^n}\;|f(x)|^pNu(x)dx$$ for certain rough singular integral T and maximal singular integral $T^*$. Here u is a nonnegative measurable function on $R^n$ and N denotes some maximal operator. As a consequence, some vector valued inequalities for both T and $T^*$ are obtained. We shall also get a boundedness result of T on the Triebel-Lizorkin spaces.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.751-753
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• 1996

The $H_{2}$/$H_{\infty}$ robust controller is designed by using polynomial approach. This controller can minimise a $H_{2}$ norm of error under the fixed bound of $H_{\infty}$ norm of mixed sensitivity function by employing the Youla parameterization and using polynomial approach at the same time. It is easy to apply this controller to adaptive system.

• Korean Journal of Mathematics
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• 제14권2호
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• pp.137-160
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• 2006

We describe the weight functions for which Hardy's inequality of nonincreasing functions is satisfied. Further we characterize the pairs of weight functions $(w,v)$ for which the Laplace transform $\mathcal{L}f(x)={\int}^{\infty}_0e^{-xy}f(y)dy$, with monotone function $f$, is bounded from the weighted Lebesgue space $L^p(w)$ to $L^q(v)$.

• 한국전산응용수학회:학술대회논문집
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• 한국전산응용수학회 2003년도 KSCAM 학술발표회 프로그램 및 초록집
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• pp.13.2-13
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• 2003

We propose some properties of Bayesian fuzzy hypotheses testing by revision for prior possibility distribution and posterior possibility distribution using weighted fuzzy hypotheses versus on with loss function.