• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2208-2211
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• 2003

In this paper, a variable bandwidth filter(VBF) is realized with the purpose of the decomposition of speech signals with time-varying instantaneous of frequencies. The proposed VBF can extract AM-FM components of a speech signal whose time-frequency representations(TFRs) are not overlapped in time-frequency domain

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.585-598
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• 2007

It is so difficult to get complete data when we conduct a questionaire in actuality. And we get inefficient results if we analyze statistical tests with ignoring missing values. Therefore, we use imputation methods which evaluate quality of data. This study proposes a imputation method by decomposition and voting with ordinal data. First, data are sorted by each variable. After that, imputation methods are used by each decomposition level. And the last step is selection of values with voting. The proposed method is evaluated by accuracy and RMSE. In conclusion, missing values are related to each variable, median imputation method using decomposition and voting is powerful.

• Speech Sciences
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• v.8 no.4
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• pp.45-58
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• 2001

Modulated components of a speech signal are frequently used for speech coding, speech recognition, and speech synthesis. Time-frequency representation (TFR) reveals some information about instantaneous frequency, instantaneous bandwidth and boundary of each component of the considering speech signal. In many cases, the extraction of AM-FM components corresponding to instantaneous frequencies is difficult since the Fourier spectra of the components with time-varying instantaneous frequency are overlapped each other in Fourier frequency domain. In this paper, an efficient method decomposing speech signal into AM-FM components is proposed. A variable bandwidth filter is developed for the decomposition of speech signals with time-varying instantaneous frequencies. The variable bandwidth filter can extract AM-FM components of a speech signal whose TFRs are not overlapped in timefrequency domain. Also, amplitude and instantaneous frequency of the decomposed components are estimated by using Hilbert transform.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.795-801
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• 2011

In machine learning and statistics it is often the case that some variables are not important, while some variables are more important than others. We propose a novel algorithm for selecting such relevant variables in the kernel Cox regression. We employ the weighted version of ANOVA decomposition kernels to choose optimal subset of relevant variables in the kernel Cox regression. Experimental results are then presented which indicate the performance of the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.201-209
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• 2013

For censored regression, it is often the case that some input variables are not important, while some input variables are more important than others. We propose a novel algorithm for selecting such important input variables for censored kernel regression, which is based on the penalized regression with the weighted quadratic loss function for the censored data, where the weight is computed from the empirical survival function of the censoring variable. We employ the weighted version of ANOVA decomposition kernels to choose optimal subset of important input variables. Experimental results are then presented which indicate the performance of the proposed variable selection method.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.4
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• pp.305-316
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• 2014

The Hodge-Helmholtz decomposition splits a vector field into the unique sum of a divergence-free vector field (solenoidal part) and a gradient field (irrotational part). In a bounded domain, a boundary condition needs to be supplied to the decomposition. The decomposition with the non-penetration boundary condition is equivalent to solving the Poisson equation with the Neumann boundary condition. The Gibou-Min method is an application of the Poisson solver by Purvis and Burkhalter to the decomposition. Using the $L^2$-orthogonality between the error vector and the consistency, the convergence for approximating the divergence-free vector field was recently proved to be $O(h^{1.5})$ with step size h. In this work, we analyze the convergence of the irrotattional in the decomposition. To the end, we introduce a discrete version of the Poincare inequality, which leads to a proof of the O(h) convergence for the scalar variable of the gradient field in a domain with general intersection property.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.793-800
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• 2004

The purpose of this study is to develope a servo system with faster and more accurate response. This paper describes a method of approximate reasoning for fuzzy control of servo system based on the decomposition of $\alpha$-level fuzzy sets. We propose that fuzzy logic algorithm is a body from fuzzy inference to defuzzificaion cases where the output variable u directly is generated PWM The effectiveness for robust and faster response of the fuzzy control scheme are verified for a variable parameter by comparison with a PID control and fuzzy control A position control of DC servo system with a fuzzy logic controller is demonstrated successfully.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.90-90
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• 2011

Long-term nonstationary oscillations (NSOs) are commonly observed in hydrological and climatological data series such as low-frequency climate oscillation indices and precipitation dataset. In this work, we present a stochastic model that captures NSOs within a given variable. The model employs a data-adaptive decomposition method named empirical mode decomposition (EMD). Irregular oscillatory processes in a given variable can be extracted into a finite number of intrinsic mode functions with the EMD approach. A unique data-adaptive algorithm is proposed in the present paper in order to study the future evolution of the NSO components extracted from EMD.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.7
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• pp.78-91
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• 1998

This paper presents modular design techniques of multiple-valued logic functions about the function decomposition method and input variable management method. The function decomposition method takes avantage of the property of the column multiplicity in a single-column variable partitioning. Due to the increased number of identical modules, we can achieve a simpler circuit design by using a single T-gate, which can eliminate some of the control functions in the module libraty types. The input variable management method is to reduce the complexity of the input variables by proposing the look up table which assign input variables to a code. In this case as the number of sub-functions increase the code-length and the size of the code-assignment table grow. We identify some situations where shard input variables among sub-functions can be further reduced by a simplicication technique. According to the result of adapting this method to a function, we have demonstrated the superiority of the proposed methods which is bing decreased to about 12% of interconnection and about 16% of T-gate numbers compare with th eexisting for th enon-symmetric and irregular function realization.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.492-492
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• 2000

This paper proposes LQ optimal controller design method based on the modal decomposition. Here, the design problem of linear time-invariant systems is considered by using pencil model. The mathematical model based on matrix pencil is one of the most general representation of the system. By adding some conditions the model can be reduced to traditional system models. In pencil model, the state feedback is considered as an algebraic constraint between the state variable and the control input variable. The algebraic constraint on pencil model is called purely static mode, and is included in infinite mode. Therefore, the information of the constant gain controller is included in the purely static mode of the augmented system which consists of the plant and the control conditions. We pay attention to the coordinate transformation matrix, and LQ optimal controller is derived from the algebraic constraint of the internal variable. The proposed method is applied to the numerical examples, and the results are verified.