• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.27-30
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• 1996

A recursive estimation for the enhancement of white noise contaminated speech is proposed. This method is based on the Kalman filter with time-varying parametric model for the clean speech signal. Then, hidden filter model are used to model the clean speech signal. An approximation improvement of 4-5 dB in SNR is achieved at 5 and 10 dB input SNR, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.1
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• pp.31-37
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• 2013

This study aims to find the optimal skirt dimensions for a composite pressure vessel with a separated dome part. The size optimization for the skirt structure of the composite pressure vessel was conducted using a sub-problem approximation method and batch processing codes programmed using ANSYS Parametric Design Language (APDL). The thickness and length of the skirt part were selected as design variables for the optimum analysis. The objective function and constraints were chosen as the weight and the displacement of the skirt part, respectively. The numerical results showed that the weight of the skirt of a composite pressure vessel with a separated dome part could be reduced by a maximum of 4.38% through size optimization analysis of the skirt structure.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.316-321
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• 2003

Recently, support vector learning attracts great interests in the areas of pattern classification, function approximation, and abnormality detection. It is well-known that among the various support vector learning methods, the so-called no-versions are particularly useful in cases that we need to control the total number of support vectors. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and a no-version support vector learning called $\nu-SVR$. After reviewing $\varepsilon-SVR$, $\nu-SVR$, and a semi-parametric approach, this paper presents an extension of the conventional $\nu-SVR$ method toward the direction that can utilize Predetermined basis functions. Moreover, the applicability of the presented method is illustrated via an example.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.23-35
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• 2014

Recently, novel application areas in digital geometry processing, such as simulation, dynamics, and medical surgery simulations, have necessitated the representation of not only the surface data but also the interior volume data of a given 3D object. In this paper, we present an efficient framework for the shape approximations of spherical solid objects based on trivariate B-splines. To do this, we first constructed a smooth correspondence between a given object and a unit solid cube by computing their harmonic mapping. We set the unit solid cube as a rectilinear parametric domain for trivariate B-splines and utilized the mapping to approximate the given object with B-splines in a coarse-to-fine manner. Specifically, our framework provides user-controllability of shape approximations, based on the control of the boundary condition of the harmonic parameterization and the level of B-spline fitting. Experimental results showed that our method is efficient enough to compute trivariate B-splines for several models, each of whose topology is identical to a solid sphere.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.163-168
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• 2010

A linguistic case-based fuzzy reasoning (LCBFR) based on standardized parametric membership functions (SPMF) is proposed. It provides an efficient mechanism for a fuzzy reasoning within linear time complexity. Thus, it can be used to improve the speed of fuzzy reasoning. In the process of LCBFR, linguistic case indexing and retrieval based on SPMF is suggested. It can be processed relatively fast compared to the previous linguistic approximation methods. From the engineering viewpoint, it may be a valuable advantage.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.10a
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• pp.136-140
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• 2000

It is desirable to predict springback quantitatively and accurately for the tool and process design in sheet stamping operations, however, it is blown very difficult. The result of springback analysis by the finite element method is sensitively influenced by numerical factors such as blank element size, number of integration point, punch velocity, contact algorithm etc. In the present work, a parametric study by Taguchi method is performed in order to evaluate the influence of numerical factors on springback Quantitatively and to obtain the combination of numerical factors which yields the best approximation to experimental data. Since springback is determined by the residual stress after forming process, it is important to evaluate stress distribution accurately. The oscillation in the time history curve of stress obtained by explicit FEM says that the stress solution at termination time is in very unstable state. Therefore, a variability study is also carried out in this study in order to assess the stability of implicit springback analysis starting from the stress solution by explicit forming simulation. The 2D draw bending process, one of the NUMISHEET '93 benchmark problems, is adopted as an application model.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.31-38
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• 1996

Many efforts for finding smooth curves and surfaces satisfying given constraints have been made, and interpolation and approximation theories with the help of computers have played an important role in this endeavour. Most research in curve and surface modeling has been largely dominated by the theory of parametric representations. While they have been successfully used in representing physical objects, parametric surfaces are confronted with some problems when objects are represented and manipulated in geometric modeling systems. In recent year, increasing attention has been paid to implicit algebraic surfaces since they are often more effective than parametric surfaces are. In this paper, we summarize the geometric properties and computational processes of objects represented using implicit algebraic functions and explain of the implementation of design tools which can design curves and surfaces of revolution. These surfaces of revolution are played an importance role in effective areas such as CAD and CAM.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.422-425
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• 1997

We consider the robust control problem for nonminimum phase(NMP) systems with parametric uncertainty which appear often in aircraft and missile control. First, a new method that makes such an uncertain NMP system to be factored as a interval minimum phase(MP) transfer function and a time delay term in the Pade approximation form has been presented. The controller to be proposed consists of a compensator $C_{Q}$(s) with Smith predictor in the internal model control(IMC) structure, so that it can have good robustness and performance against the structured uncertainty and the time delay behaviour due to NMP plant the $C_{Q}$(s) is designed on the MP model by using QFT. The stability and performance of overall system has been evaluated by the generalized Kharitonov theorem.rem.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.465-468
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• 2001

MPEG-4 Parametric Coding 중 저 비트율로 음성신호를 부호화하는 HVXC(Harmonic Vector excitation Ending)의 복호화 모듈인 LSP 합성필터와 무성음 합성부, 유성음 합성부를 VHDL을 이용하여 구현하였다. MPEG-4 HVXC의 복호화 과정은 코드북을 이용하여 LSP 계수, VXC signal, 그리고 Spectral Envelop이 복호화 되어 각각 LSP 역필터, 무성음과 유성음 합성단을 통과하여 LPC계수와 유,무성음 여기신호로 변환된 후 LPC 합성필터링 과정을 거쳐 최종적으로 음성신호를 출력시킨다. LSP inverse filter에서 사용되는 cosine함수값을 위하여 Table based Approximation을 이용하여 적은 양의 Table 값을 사용하여 정확하고 고속의 cosine 연산을 수행하였다. VXC 복호화 과정에서는 신호의 중복성을 제거하는 Hidden Address in LSH 방법을 사용하여 코드북의 크기를 줄였다. 유성음 합성단에서는 IFFT 모듈을 이용하여 연산속도를 증가 시켰다. 최종적으로 위와 같이 구현된 시스템을 Simulation을 통해 Software 검증을 하였다.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.607-617
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• 2003

This paper offers a practical comparison of efficiency between local likelihood approach and conventional kernel approach in density estimation. The local likelihood estimation procedure maximizes a kernel smoothed log-likelihood function with respect to a polynomial approximation of the log likelihood function. We use two types of data driven bandwidths for each method and compare the mean integrated squares for several densities. Numerical results reveal that local log-linear approach with simple plug-in bandwidth shows better performance comparing to the standard kernel approach in heavy tailed distribution. For normal mixture density cases, standard kernel estimator with the bandwidth in Sheather and Jones(1991) dominates the others in moderately large sample size.