• Journal of KSNVE
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• v.7 no.5
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• pp.773-780
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• 1997

Using Generalized Inverse Method presented by Udwadia and Kalaba in 1992, we can obtain equations to exactly describe the motion of constrained systems. When the differential equations are numerically integrated by any numerical integration scheme, the numerical results are generally found to veer away from satisfying constraint equations. Thus, this paper deals with the numerical integration of the differential equations describing constrained systems. Based on Baumgarte method, we propose numerical methods for reducing the errors in the satisfaction of the constraints.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.807-812
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• 2007

Recently, Extreme learning machine(ELM), a novel learning algorithm which is much faster than conventional gradient-based learning algorithm, was proposed for single-hidden-layer feedforward neural networks. The initial input weights and hidden biases of ELM are usually randomly chosen, and the output weights are analytically determined by using Moore-Penrose(MP) generalized inverse. But it has the difficulties to choose initial input weights and hidden biases. In this paper, an advanced method using the bacterial foraging algorithm to adjust the input weights and hidden biases is proposed. Experiment at results show that this method can achieve better performance for problems having higher dimension than others.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.37-48
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• 1995

This paper presents an sstimation of ARMA coefficients of noisy ARMA system using generalized total least square (GTLS) method. GTLS problem for ARMA system is defined as minimizing the errors between the noisy output vectors and estimated noisy-free output. The GTLS problem is solved in closed form by eigen-problem and the perturbation analysis of GTLS is presented. Also its recursive solution (recursive GTLS) is proposed using the power method and the covariance formula of the projected output error vector into the input vector space. The simulation results show that GTLS ARMA coefficients estimator is an unbiased estimator and that recursive GTLS achieves fast convergence.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.154-162
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• 1997

본 논문은 구속된 기계 시스템의 운동 제어 설계를 위한 새로운 방법을 제안한다. 구속된 기계 시스템의 운동 제어에는 지금까지 주로 사용되어온 Lagrange의 운동 방정식에 의한 모델링 보다 Udwadia와 Kalaba에 의해 제안된 운동 방정식에 의한 모델링이 더욱 적합함을 보였으며 이는 Holonomic 및 Nonholonomic 구속 조건을 비롯한 대부분의 구속 조건이 포함된다. 문헌에 잘 알려진 두 시스템을 시뮬레이션을 통하여 비교 함으로써 본 논문에 제안된 방법이 보다 우수한 결과를 보여줌을 확인 할 수 있었다. 또한 지금까지 불가능 하였던 비선형 일반 속도(gereralized velocity)를 포함한 구속 조건도 용이하게 제어됨을 보임으로써 광범위한 구속된 기계 시스템의 제어 문제를 통일된 방법으로 접근 할 수 있음을 제시하였다.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.11-18
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• 2009

This paper proposes the way of improving learning speed in Levenberg-Marquardt algorithm using the principal submatrix of Jacobian matrix. The Levenberg-Marquardt learning uses Jacobian matrix for Hessian matrix to get the second derivative of an error function. To make the Jacobian matrix an invertible matrix. the Levenberg-Marquardt learning must increase or decrease ${\mu}$ and recalculate the inverse matrix of the Jacobian matrix due to these changes of ${\mu}$. Therefore, to have the proper ${\mu}$, we create the principal submatrix of Jacobian matrix and set the ${\mu}$ as the eigenvalues sum of the principal submatrix. which can make learning speed improve without calculating an additional inverse matrix. We also showed that our method was able to improve learning speed in both a generalized XOR problem and a handwritten digit recognition problem.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.127-132
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• 1998

Mobile wheeled robots are nonholonomically constrained systems. Generally, it is very difficult to describe the motion of mechanical systems with nonintegrable nonholonomic constraints. An objective of this study is to describe the motion of a robot with a free wheel. The motion of holonomically and/or nonholonomically constrained system can be simply determined by Generalized Inverse Method presented by Udwadia and Kalaba in 1992. Using the method, we describe the exact motion of the robot and determine the constraint force exerted on the robot for satisfying constraints imposed on it. The application illustrates the ease with which the Generalized Inverse Method can be utilized for the purpose of control of nonlinear system without depending on any linearization, maintaining precision tracking motion and explicit determination of control forces of nonholonomically constrained system.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.259-259
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• 2003

Genetic algorithms using a Process of genetic evolution of an organism are appropriate for hard problems that have not been solved by any deterministic method. Up to now, the controller design method has been made with the frequency dependent specification but the design method with the time specification has gotten little progress. In this paper, we study the controller design to satisfy the performance of a plant using the generalized Manabe standard form. When dealing with a controller design in the case of two parameter configurations, there are some situations that neither a known pseudo inverse technique nor the inverse method can be applicable. In this case, we propose two methods of designing a controller by the gradient algorithm and the new pseudo inverse method so that the desired closed polynomials are either equalized to or approximated to the designed polynomial. Design methods of the proposed controller are implemented in Java.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.269-275
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• 2013

In this paper, a new modeling method of a magnetic levitation(Maglev) system using extreme learning machine(ELM) is proposed. The linearized methods using Taylor Series expansion has been used for modeling of a Maglev system. However, the numerical method has some drawbacks when dealing with the components with high nonlinearity of a Maglev system. To overcome this problem, we propose a new modeling method of the Maglev system with electro magnetic suspension, which is based on ELM with fast learning time than conventional neural networks. In the proposed method, the initial input weights and hidden biases of the method are usually randomly chosen, and the output weights are analytically determined by using Moore-Penrose generalized inverse. matrix Experimental results show that the proposed method can achieve better performance for modeling of Maglev system than the previous numerical method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.8
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• pp.41-46
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• 2006

The capability for reconstructing impact forces of an aircraft wing using impact response functions and regularization methods were examined. The impact response function which expresses the relation between the structure response and the impact force was derived using the information on mass and stiffness data of a finite element model for the wing. Iterative Tikhonov regularization method and generalized singular value decomposition method were used to inverse the impact response function that was generally ill-posed. For the numerical verification, a fighter aircraft wing was used. Strain and deflection histories obtained from finite element analysis were compared with the results calculated using impact response functions. And the impact forces were reconstructed with the strain histories obtained from finite element analysis. The numerical verification results showed that this method can be used to monitor impact forces on aircraft structures.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.69-78
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• 2017

Shannon of the 5G smartphone and Fourier of the signal processing meet in the sampling theorem (2 times the highest frequency 1). In this paper, the initial Shannon Theorem finds the Shannon capacity at the point-to-point, but the 5G shows on the Relay channel that the technology has evolved into Multi Point MIMO. Fourier transforms are signal processing with fixed parameters. We analyzed the performance by proposing a 2N-1 multivariate Fourier-Jacket transform in the multimedia age. In this study, the authors tackle this signal processing complexity issue by proposing a Jacket-based fast method for reducing the precoding/decoding complexity in terms of time computation. Jacket transforms have shown to find applications in signal processing and coding theory. Jacket transforms are defined to be $n{\times}n$ matrices $A=(a_{jk})$ over a field F with the property $AA^{\dot{+}}=nl_n$, where $A^{\dot{+}}$ is the transpose matrix of the element-wise inverse of A, that is, $A^{\dot{+}}=(a^{-1}_{kj})$, which generalise Hadamard transforms and centre weighted Hadamard transforms. In particular, exploiting the Jacket transform properties, the authors propose a new eigenvalue decomposition (EVD) method with application in precoding and decoding of distributive multi-input multi-output channels in relay-based DF cooperative wireless networks in which the transmission is based on using single-symbol decodable space-time block codes. The authors show that the proposed Jacket-based method of EVD has significant reduction in its computational time as compared to the conventional-based EVD method. Performance in terms of computational time reduction is evaluated quantitatively through mathematical analysis and numerical results.