• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.85-92
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• 2017

This paper presents a dehazing method based on a fuzzy membership function and variational method. The proposed algorithm consists of three steps: i) estimate transmission through a pixel-based operation using a fuzzy membership function, ii) refine the transmission using an L1-norm-based regularization method, and iii) obtain the result of haze removal based on a hazy image formation model using the refined transmission. In order to prevent color distortion of the sky region seen in conventional methods, we use a trapezoid-type fuzzy membership function. The proposed method acquires high-quality images without halo artifacts and loss of color contrast.

• IE interfaces
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• v.24 no.2
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• pp.151-155
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• 2011

In this study, we propose a signomial classification method with ₀-regularization (₀-)which seeks a sparse signomial function by solving a mixed-integer program to minimize the weighted sum of the ₀-norm of the coefficient vector of the resulting function and the $L_1$-norm of loss caused by the function. $SC_0$ gives an explicit description of the resulting function with a small number of terms in the original input space, which can be used for prediction purposes as well as interpretation purposes. We present a practical implementation of $SC_0$ based on the mixed-integer programming and the column generation procedure previously proposed for the signomial classification method with $SL_1$-regularization. Computational study shows that $SC_0$ gives competitive performance compared to other widely used learning methods for classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5103-5115
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• 2015

In radar imaging, a target is usually consisted of a few strong scatterers which are sparsely distributed. In this paper, an improved sparse signal recovery algorithm based on smoothed l₀ (SL0) norm method is proposed to achieve high resolution ISAR imaging with limited pulse numbers. Firstly, one new smoothed function is proposed to approximate the l₀ norm to measure the sparsity. Then a single loop step is used instead of two loop layers in SL0 method which increases the searching density of variable parameter to ensure the recovery accuracy without increasing computation amount, the cost function is undated in every loop for the next loop until the termination is satisfied. Finally, the new set of solution is projected into the feasible set. Simulation results show that the proposed algorithm is superior to the several popular methods both in terms of the reconstruction performance and computation time. Real data ISAR imaging obtained by the proposed algorithm is competitive to several other methods.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.5
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• pp.39-48
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• 2009

Many super-resolution reconstruction algorithms have been proposed since it was the first proposed in 1984. The spatial domain approach of the super-resolution reconstruction methods is accomplished by mapping the low resolution image pixels into the high resolution image pixels. Generally, a super-resolution reconstruction algorithm by using the spatial domain approach has the noise problem because the low resolution images have different noise component, different PSF, and distortion, etc. In this paper, we proposed the new super-resolution reconstruction method that uses the L1 norm to minimize noise source and also uses the Huber norm to preserve edges of image. The proposed algorithm obtained the higher image quality of the result high resolution image comparing with other algorithms by experiment.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1051-1059
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• 1992

Two types of digital repetitive control systems are analyzed and designed to reduce the error spectrum including not only harmonic but also non-harmonic components. First, a novel gain scheduling algorithm is suggested for conventional and modified repetitive controller is scheduled to reduce the infinite norm of error in frequency domain. For this, the relative error transfer function is mewly defined as the ratio of the error spectrum for the system with a repetitive controller to the error spectrum for the system with a repetitive controller to the error spectrum for the system without a repetitive controller. Secondly, as an alternative of a repetitive control system with the gain scheduling, a repetitive control system with higher order repetitve function is analyzed and designed, where instead of equal weightings, weightings of the higher order repetitive function is determined in such a way that the infinite norm of relative error transfer function is minimized. To show the validities of proposed methods, computer simulation results are illustrated for a typical disk drive head positioning servo system.

• Journal of the Korean Mathematical Society
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• v.56 no.5
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• pp.1387-1401
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• 2019

Consider a finite measure space (${\Omega}$, ${\Sigma}$, ${\mu}$) and a Banach space $X({\mu})$ consisting of (equivalence classes of) real measurable functions defined on ${\Omega}$ such that $f{\chi}_A{\in}X({\mu})$ and ${\parallel}f{\chi}_A{\parallel}{\leq}{\parallel}f{\parallel}$, ${\forall}f{\in}({\mu})$, $A{\in}{\Sigma}$. We prove that if it satisfies the subsequence property, then it is an ideal of measurable functions and has an equivalent norm under which it is a Banach function space. As an application we characterize norms that are equivalent to a Banach function space norm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.8
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• pp.1898-1909
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• 1993

In this paper, a convenient scheme for solving multi-objective optimization problems including fuzzy information in both objective functions and constraints is presented. At first, a multi-objective problem is converted into single objective problem based on the norm method, and a merbership function is constructed by selecting its type and providing the parameters defined by the norm method. Finally, this fuzzy programming problem is converted into an ordinary optimization problem which can be solved by usual nonlinear programming techniques. With this scheme, a designer can conveniently obtain pareto optimal solutions of a fuzzy system only by providing some parameters corresponding to the importance of the objectiv functions. Proposed scheme is simple and efficient in treating multi-objective fuzzy systems compared with and method by with membership function value is provided interactively. To show the validity of the scheme, a simple 3-bar truss example and optimal cutting problem are solved, and the results show that the scheme is very useful and easy to treat multi-objective fuzzy systems.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.271-282
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• 1996

this paper deal with the estimation of the power spectral density function of time series. A kernel estimator which is based on local average is defined and the rates of convergence of the pointwise, $$L_2$-norm; and; $L{\infty}$-norm associated with the estimator are investigated by restricting as to kernels with suitable assumptions. Under appropriate regularity conditions, it is shown that the optimal rate of convergence for 0$N^{-r}$ both in the pointwiseand $$L_2$-norm, while; $N^{r-1}(logN)^{-r}$is the optimal rate in the $L{\infty}-norm$. Some examples are given to illustrate the application of main results.

• Bulletin of the Korean Mathematical Society
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• v.58 no.1
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• pp.205-215
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• 2021

In [1], Beznosova proved that the bound on the norm of the dyadic paraproduct with b ∈ BMO in the weighted Lebesgue space L2(w) depends linearly on the Ad2 characteristic of the weight w and extrapolated the result to the Lp(w) case. In this paper, we provide the weighted norm estimates of the dyadic paraproduct πb with b ∈ VMO and reduce the dependence of the Ad2 characteristic to 1/2 by using the property that for b ∈ VMO its mean oscillations are vanishing in certain cases. Using this result we also reduce the quadratic bound for the commutators of the Calderón-Zygmund operator [b, T] to 3/2.

• Bulletin of the Korean Mathematical Society
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• v.47 no.4
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• pp.777-785
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• 2010

Let X be a linear space and Y be a complete quasi p-norm space. We will show that for each function f : X $\rightarrow$ Y, which satisfies the inequality ${\parallel}{\Delta}_x^nf(y)\;-\;n!f(x){\parallel}\;{\leq}\;\varphi(x,y)$ for suitable control function $\varphi$, there is a unique monomial function M of degree n which is a good approximation for f in such a way that the continuity of $t\;{\mapsto}\;f(tx)$ and $t\;{\mapsto}\;\varphi(tx,\;ty)$ imply the continuity of $t\;{\mapsto}\;M(tx)$.