• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.79-90
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• 2004

Systematical robust stability analysis and design scheme for the feedback linearization control systems via fuzzy modeling are proposed. It is considered that uncertainty and disturbances are included in the Takagi-Sugeno fuzzy models representing the nonlinear plants. Robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions and by converting the analysis and design problems into the linear matrix inequality optimization, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.177-187
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• 1997

This article considers the power performance of the tests in unbalanced two way mixed linear models with one fixed factor. The generalized least squares (GLS) F statistic testing no differences among the effects of the levels of the fixed factor is estimated using Henderson's method III, minimum norm quadratic unbiased estimator (MINQUE) with prior guess 1, maximum likelihood (ML) and resticted maximum likelihood (REML). We investigate the power performance of these test statistics. It can be shown, through simulation, that the GLS F statistics using four estimators produce similar type I error rates and power performance.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.529-531
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• 2005

A block-based fast motion estimation algorithm is proposed in this paper to perform motion estimation based on the efficiently reduced search ranges in MPEG-4(ERS). This algorithm divides the search areas into several small search areas and the candidate small search area that has the lowest average of sum norm difference between current macroblock and candidate macroblock is chosen to perform block motion estimation using the Nobel Successive Elimination Algorithm (NSEA). Experimental results of the proposed algorithm show that the averaging PSNR improvement is better maximum 0.125 dB than other tested algorithms and bit saving effect is maximum 20kbps for some tested sequences in low-bit rate circumstance.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.5
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• pp.277-281
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• 2013

Modern speaker verification systems based on support vector machines (SVMs) use Gaussian mixture model (GMM) supervectors as their input feature vectors, and the maximum a posteriori (MAP) adaptation is a conventional method for generating speaker-dependent GMMs by adapting a universal background model (UBM). MAP adaptation requires the appropriate amount of input utterance due to the number of model parameters to be estimated. On the other hand, with limited utterances, unreliable MAP adaptation can be performed, which causes adaptation noise even though the Bayesian priors used in the MAP adaptation smooth the movements between the UBM and speaker dependent GMMs. This paper proposes a sparse MAP adaptation method, which is known to perform well in the automatic speech recognition area. By introducing sparse MAP adaptation to the GMM-SVM-based speaker verification system, the adaptation noise can be mitigated effectively. The proposed method utilizes the L0 norm as a regularizer to induce sparsity. The experimental results on the TIMIT database showed that the sparse MAP-based GMM-SVM speaker verification system yields a 42.6% relative reduction in the equal error rate with few additional computations.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.582-589
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• 2003

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included Un the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.225-235
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• 2005

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.12-22
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• 1996

A numerous designs of PI controllers have been suggested to solve out trade-off between tracing and regulating problems. We constructed the PI controller system with two-degree-of-freedom that is more analytic and a better approach to a practical one. In the conventional H$_{2}$ design of optimal PI controllers, the cost function includes only the plant output terms due to the divergent problems. Since the platn input temr is not considered in PI controller design, occasionally, the plant input thends to be either very large or saturated. To solve the prior mentioned problems, we employed a mixed $H_2/H_{\infty}$ method that combines the H$_{2}$ design method to decide optimal parameters of PI controller and the $H_2/H_{\infty}$ design method to minimize the maximum amplitude of plant input. The calculation time of the H$_{infty}$ norm was considerably reduced by the simple scalar function obtained by the wiener-hopf factorization of non-scalar functions.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.64-71
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• 1994

In this paper, we propose orthogonal integer transform(OIT) with general form. Considering the orthogonality and magnitude value order of the DCT Matrix whose performance is found to be close to that of the KLT, known to be optimal. The proposed OIT matrix is composed of values minimizing Hibert-Schmidt norm among integer values which satisfy the condition of orthogonality and the relative magnitudes of the DCT matrix. Comparing the OIT with the DCT, CMT, and ICT in error characteristics, transform efficiency, and maximum reducible bit, it is shown that the performance of the OIT compares more closely to that of the KLT relative to the performances of the DCT, CMT, and ICT when N=8.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.501-506
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• 1993

An efficient solution algorithm of the optimal load distribution problem with joint torque constraints is presented. Multiple robot system where each robot is rigidly grasping a common object is considered. The optimality criteria used is the sum of weighted norm of the joint torque vectors. The maximum and minimum bounds of each joint torque in arbitrary form are considered as constraints, and the solution that reduces the internal force to zero is obtained. The optimal load distribution problem is formulated as a quadratic optimization problem in R, where I is the number of robots. The general solution can be obtained using any efficient numerial method for quadratic programming, and for dual robot case, the optimal solution is given in a simple analytical form.

• Journal of applied mathematics & informatics
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• v.33 no.5_6
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• pp.485-502
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• 2015

A computational method for solving singularly perturbed boundary value problem of differential equation with shift arguments of mixed type is presented. When shift arguments are sufficiently small (o(ε)), most of the existing method in the literature used Taylor's expansion to approximate the shift term. This procedure may lead to a bad approximation when the delay argument is of O(ε). The main idea for this work is to deal with constant shift arguments, which are independent of ε. In the present method, we construct the formally asymptotic solution of the problem using the method of composite expansion. The reduced problem is solved numerically by using operator compact implicit method, and the second problem is solved analytically. Error estimate is derived by using the maximum norm. Numerical examples are provided to support the theoretical results and to show the efficiency of the proposed method.