• Structural Engineering and Mechanics
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• v.57 no.2
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• pp.281-294
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• 2016

The paper is devoted to study a mesh-free analysis method of structural elements of engineering structures based on B-spline Wavelet Basis Function. First, by employing the moving-least square method and the weighted residual method to solve the structural displacement field, the control equations and the stiffness equations are obtained. And then constructs the displacement field of the structure by using the m-order B-spline wavelet basis function as a weight function. In the end, the paper selects the plane beam structure and the structure with opening hole to carry out numerical analysis of deformation and stress. The Finite Element Method calculation results are compared with the results of the method proposed, and the calculation results of the relative error norm is compared with Gauss weight function as weight function. Therefore, the clarification verified the validity and accuracy of the proposed method.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1660-1668
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• 2004

This paper proposes a Voice Activity Detection (VAD) algorithm based on Radial Basis Function (RBF) network using dual threshold. The k-means clustering and Least Mean Square (LMS) algorithm are used to upade the RBF network to the underlying speech condition. The inputs for RBF are the three parameters in a Code Exited Linear Prediction (CELP) coder, which works stably under various background noise levels. Dual hangover threshold applies in BRF-VAD for reducing error, because threshold value has trade off effect in VAD decision. The experimental result show that the proposed VAD algorithm achieves better performance than G.729 Annex B at any noise level.

• Journal of KIISE:Software and Applications
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• v.27 no.9
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• pp.913-919
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• 2000

본 논문에서는 인간 시지각을 고려한 새로운 영상 압축 방법을 제시한다. 영상의 화소의 값들이 x-y 평명상에서 정의된 3차원 곡면 위에 있는 점들로 가정하여, 영상을 곡면의 복잡도에 따라 나누고, 나누어진 각각의 곡면(영역)은 Radial-Basis Function (RBF)를 사용하여 근사화하는 방법으로 영상을 압축한다. 본 방법은 JPEG 압축 방법과 비슷한 압축율과 영상의 질을 얻을 수 있다.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.601-608
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• 2007

Lee, et al. (1999) proposed a unique but universal robust objective function replacing the square objective function for the radial basis function network, and demonstrated some advantages. In this article, the robust objective function in Lee, et al. (1999) is adapted for a multilayer perceptron (MLP). The shape of the robust objective function is formed by the scale parameter. Another method of determining a proper value of that parameter is proposed.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.121-124
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• 2009

A moving mesh system is one of the critical parts in a computational fluid dynamics analysis. In this study, the RBF(Radial Basis Function) which shows better performance than hybrid meshes was developed to obtain the deformed grid. The RBF method can handle large mesh deformations caused by translations, rotations and deformations, both for 2D and 3D meshes. Another advantage of the method is that it can handle both structured and unstructured grids with ease. The method uses a volume spline technique to compute the deformation of block vertices and block edges, and deformed shape.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.237-238
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• 2008

퍼지 RBFNN의 설계에 있어 가장 중요한 과정인 Radial Basis Function의 결정은 퍼지 RBFNN의 모델링 성능을 좌우한다. 기존에는 FCM을 이용하여 Radial Basis Function의 초기 위치를 결정하고 오류 역전파 알고리즘과 같은 최적화 알고리즘을 이용하여 최적의 Radial Basis Function을 결정하였다. 근래에는 Conditional FCM을 이용하여 출력공간에 정의된 정보입자의 정보를 이용하여 입력공간상에서 Radial Basis Function의 위치를 결정하여 퍼지 RBFNN의 성능을 개선시키고자 하는 연구 수행되어졌다. 그러나 출력공간상에서 얻은 정보입자를 입력공간상으로 정보 손실없이 전달할 수 없어서 기대한 만큼의 성능 개선을 이룰 수 없었다. 이를 개선하기 위해 출력 공간예서 정의된 정보 입자를 정보 손실없이 입력 공간에 투영하기 위하여 퍼지 kNN기법을 도입하여 새로운 퍼지 RBFNN 설계 방법을 제안한다.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.452-460
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• 2005

Based on an introduced optimal trajectory planning method, this paper mainly deals with the accuracy analysis during the function approximation process of the optimal trajectory planning method. The basis functions are composed of Hermit polynomials and Fourier series to improve the approximation accuracy. Since the approximation accuracy is affected by the given orders of each basis function, the accuracy of the optimal solution is examined by changing the combinations of the orders of Hermit polynomials and Fourier series as the approximation basis functions. As a result, it is found that the proper approximation basis functions are the $5^{th}$ order Hermit polynomials and the $7^{th}-10^{th}$ order of Fourier series.

• Interaction and multiscale mechanics
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• v.2 no.4
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• pp.333-352
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• 2009

We introduce a radial basis collocation method to solve axially moving beam problems which involve $2^{nd}$ order differentiation in time and $4^{th}$ order differentiation in space. The discrete equation is constructed based on the strong form of the governing equation. The employment of multiquadrics radial basis function allows approximation of higher order derivatives in the strong form. Unlike the other approximation functions used in the meshfree methods, such as the moving least-squares approximation, $4^{th}$ order derivative of multiquadrics radial basis function is straightforward. We also show that the standard weighted boundary collocation approach for imposition of boundary conditions in static problems yields significant errors in the transient problems. This inaccuracy in dynamic problems can be corrected by a statically condensed semi-discrete equation resulting from an exact imposition of boundary conditions. The effectiveness of this approach is examined in the numerical examples.