• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.5
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• pp.409-415
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• 2013

In this paper, we propose a correlation function using newly designed local signals for cosine-phased binary offset carrier (BOC) signal tracking. First, we divide a sub-carrier pulse over one pseudo random noise code period into multiple rectangular pulses, and subsequently, design novel local signals. Then, we obtain a correlation function with no side-peak based on a combination of correlations between the newly generated local signals and received cosine-phased BOC signal. From numerical results, it is confirmed that the proposed correlation function provides a tracking performance improvement over the conventional correlation functions in terms of the tracking error standard deviation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1323-1333
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• 1997

In this paper, we propose an efficient architecture for a high-speed cell concentrator/distributor(HCCD) in an ATM(Asynchronous Transfer Mode) switch and by analyzeing the simulation results evaluate the performance of the proposed architecuture. The proposed HCCD distributes cells from a switch link to local processors, or concentrates cells from local processor s to a switch link. This design is to guarntee a high throughput for the IPC (inter-processor communication) link in a distributed ATM switching system. The HCCD is designed in a moudlar architecture to provide the extensibility and the flexibility. The main characteristics of the HCCD are 1) Adaption of a local CPU in HCCD for improving flexibility of the system, 2) A cell-baced statistical multiplexing function for efficient multiplexing, 3) A cell distribution function based on VPI(Virtual Path Identifier), 4) A bypassing capability for IPC between processor attached to the same HCCD, 5) A multicasting capability for point-to-multipoint communication, 6) A VPI table updating function for the efficient management of links, 7) A self-testing function for detecting system fault.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.532-540
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• 2001

In this paper, we propose a probabilistic tabu search strategy for function optimization. It is composed of two procedures, one is Basic search procedure that plays a role in local search, and the other is Restarting procedure that enables to diversify search region. In basic search procedure, we use Belief space and Near region to create neighbors. Belief space is made of high-rank neighbors to effectively restrict searching space, so it can improve searching time and local or global searching capability. When a solution is converged in a local area, Restarting procedure works to search other regions. In this time, we use Probabilistic Tabu Strategy(PTS) to adjust parameters such as a reducing rate, initial searching region etc., which makes enhance the performance of searching ability in various problems. In order to show the usefulness of the proposed method, the PTS is applied to the minimization problems such as De Jong functions, Ackley function, and Griewank functions etc., the results are compared with those of GA or EP.

• Journal of the Chungcheong Mathematical Society
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• v.30 no.2
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• pp.165-175
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• 2017

This paper gives an extensive study of ideal topological space and introduce two new types of set with the help of local function. Several characterizations of these sets will also be discussed through this paper and finally gives new representation of ${\alpha}$-sets and semi-open sets.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.585-594
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• 2006

We consider a stochastic integral process represented by multiple Ito-Wiener integrals. We derive gaussian chaos which has some shift continuous function. We get continuity property of self-similar process represented by multiple integrals and finally we show that $Y_{H_t}$ (t) is continuous in t with probability one for Holder function $H_t$ of exponent $\beta$.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.393-404
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• 2003

In general, a differential operator can be used as a tool of treating the local properties of given function. However, when the given function is varied with high frequency and has irregular form with non-stationary evolution it may not act its role sufficiently as in case of nowhere differentiable curves. In this paper we introduce a multi-scale derivative as a form of weakened global derivative so that it may explain its semi global diffusion properties as well as local ones for the various irregular diffusion phenomena.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.13-16
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• 2001

We compare methods for detecting influential observations that have a large influence on the likelihood ratio test statistics that the two sets of variables are uncorrelated with one another. For this purpose we derive results of the deletion diagnostic, the influence function, the standardized influence matrix and the local influence. An illustrative example is given.

• International Journal of Precision Engineering and Manufacturing
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• v.8 no.1
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• pp.3-10
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• 2007

A new approach based on implicit surface interpolation combined with domain decomposition is proposed for filling complex-shaped holes in a large polygon model, A surface was constructed by creating a smooth implicit surface from an incomplete polygon model through which the actual surface would pass. The implicit surface was defined by a radial basis function, which is a continuous scalar-value function over the domain $R^{3}$. The generated surface consisted of the set of all points at which this scalar function is zero. It was created by placing zero-valued constraints at the vertices of the polygon model. The well-known domain decomposition method was used to treat the large polygon model. The global domain of interest was divided into smaller domains in which the problem could be solved locally. The LU decomposition method was used to solve the set of small local problems; the local solutions were then combined using weighting coefficients to obtain a global solution. The validity of this new approach was demonstrated by using it to fill various holes in large and complex polygon models with arbitrary topologies.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.929-937
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• 2003

Kernel type estimations of discontinuity point at an unknown location in regression function or its derivatives have been developed. It is known that the discontinuity point estimator based on $Gasser-M\ddot{u}ller$ regression estimator with a one-sided kernel function which has a zero value at the point 0 makes a poor asymptotic behavior. Further, the asymptotic variance of $Gasser-M\ddot{u}ller$ regression estimator in the random design case is 1.5 times larger that the one in the corresponding fixed design case, while those two are identical for the local polynomial regression estimator. Although $Gasser-M\ddot{u}ller$ regression estimator with a one-sided kernel function which has a non-zero value at the point 0 for the modification is used, computer simulation show that this phenomenon is also appeared in the discontinuity point estimation.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.673-683
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• 2017

The least absolute shrinkage and selection operator (LASSO) has been a popular regression estimator with simultaneous variable selection. However, LASSO does not have the oracle property and its robust version is needed in the case of heavy-tailed errors or serious outliers. We propose a robust penalized regression estimator which provide a simultaneous variable selection and estimator. It is based on the rank regression and the non-convex penalty function, the smoothly clipped absolute deviation (SCAD) function which has the oracle property. The proposed method combines the robustness of the rank regression and the oracle property of the SCAD penalty. We develop an efficient algorithm to compute the proposed estimator that includes a SCAD estimate based on the local linear approximation and the tuning parameter of the penalty function. Our estimate can be obtained by the least absolute deviation method. We used an optimal tuning parameter based on the Bayesian information criterion and the cross validation method. Numerical simulation shows that the proposed estimator is robust and effective to analyze contaminated data.