• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.98-107
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• 2007

For high-dimensional pattern recognition, such as face classification, the small number of training samples leads to the Small Sample Size problem when the number of pattern samples is smaller than the number of dimensionality. Recently, various LDA-extensions have been developed, including LDA, PCA+LDA, and Direct-LDA, to address the problem. This paper proposes a method of improving the classification efficiency by increasing the number of (sub)-classes through pre-clustering a training set prior to the execution of Direct-LDA. In LDA (or Direct-LDA), since the number of classes of the training set puts a limit to the dimensionality to be reduced, it is increased to the number of sub-classes that is obtained through clustering so that the classification performance of LDA-extensions can be improved. In other words, the eigen space of the training set consists of the range space and the null space, and the dimensionality of the range space increases as the number of classes increases. Therefore, when constructing the transformation matrix, through minimizing the null space, the loss of discriminatve information resulted from this space can be minimized. Experimental results for the artificial data of X-OR samples as well as the bench mark face databases of AT&T and Yale demonstrate that the classification efficiency of the proposed method could be improved.

• Journal of the Korean Society of Combustion
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• v.2 no.1
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• pp.39-51
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• 1997

A review of probability density function(PDF) methodology and direct numerical simulation for the purpose of modeling turbulent combustion are presented in this study where particular attention is focused on the modeling problem of turbulent molecular mixing term appearing in PDF transport equation. Existing mixing models results were compared to those evaluated by direct numerical simulation in a turbulent premixed medium with finite rate chemistry in which the initial scalar field is composed of pockets of partially burnt gases to simulate autoignition. Two traditional mixing models, the least mean square estimations(LMSE) and Curl#s model are examined to see their prediction capability as well as their modeling approach. Test calculations report that the stochastically based Curl#s approach, though qualitatively demonstrates some unphysical behaviors, predicts scalar evolutions which are found to be in good agreement with statistical data of direct numerical simulation.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.69-71
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• 1997

The direct drive motor is directly coupled by load. So, it is directly affected by load and disturbances. To control the direct drive motor, a robust controller is need. The main feature of variable structure system is that system trajectories are robust and insensitive to parameter variations and disturbances in the sliding mode. In this paper, adaptive variable structure controller, is used for the BLDD SM(Brushless Direct Drive Servo Motor) control. The chattering problem is reduced by using the saturation function.

• Journal of Power Electronics
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• v.18 no.3
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• pp.736-745
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• 2018

This paper presents an extended state observer (ESO) based direct torque control (DTC) for use in induction motor systems to handle the issues of time delays, load torque disturbances and parameter uncertainties. Direct torque control offers an excellent torque response and it does not require a proportion integration (PI) controller in the current loop. However, a PI controller is still adopted in the outer speed loop to generate the torque reference value, which is a slow method. An ESO based compound control scheme is proposed to improve the response rate and accuracy of the torque reference signal, especially when load torque is injected. In addition, the time delay problem is analyzed and compensated for in this paper to reduce torque ripples. The proposed disturbance compensation technique based direct control scheme is shown to have good performance both in the transient and stable states via simulations and experimental results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10C
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• pp.942-947
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• 2006

In this paper, a new feature representation technique called Improved 2-directional 2-dimensional direct linear discriminant analysis (Improved $(2D)^2$ DLDA) is proposed. In the case of face recognition, thesmall sample size problem and need for many coefficients are often encountered. In order to solve these problems, the proposed method uses the direct LDA and 2-directional image scatter matrix. Moreover the selection method of feature vector and the method of similarity measure are proposed. The ORL face database is used to evaluate the performance of the proposed method. The experimental results show that the proposed method obtains better recognition rate and requires lesser memory than the direct LDA.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.79-86
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• 2008

High performance direct-iterative hybrid linear solver for large scale finite element problem is developed. Direct solution method is robust but difficult to parallelize, whereas iterative solution method is opposite for direct method. Therefore, combining two solution methods is desired to get both high performance parallel efficiency and numerical robustness for large scale structural analysis problems. Hybrid method mentioned in this paper is based on FETI-DP (Finite Element Tearing and Interconnecting-Dual Primal method) which has good parallel scalability and efficiency. It is suitable for fourth and second order finite element elliptic problems including structural analysis problems. We are using the hybrid concept of theses two solution method categories, combining the multifrontal solver into FETI-DP based iterative solver. Hybrid solver is implemented for our general structural analysis code, IPSAP.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.2
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• pp.97-111
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• 1995

In this paper, we investigate path compensation scheme for the machining errors due to tool deflection in 2D contour machining. The significance of the deflection error is first shown by experiments, and a direct compensation scheme is sought. In the presented scheme, the tool path is evaluated and correcte based on the instantaneous deflection force model, until the desired contour can be obtained under the presence of tool deflection in actual machining. In the sense that the developed method estimates and compensates the machining errors via modifying the tool path, it is distinguished from the previous approach based on geometric simulation and cutting simulation. Further, it can be viewed as a direct and active method toward direct shape control in CNC machining. Simulation results are included to show the validity and adequacy of the path-modification scheme under various cutting conditions.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.398-401
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• 2001

There are two methods to calculate design sensitivity such as direct differentiation method and adjoint method. A sort of direct differentiation method for design sensitivity analysis costs too much when number of design variables is much larger than the number of response functions whose design sensitivity analyses are required. Therefore, an adjoint method is suggested for the case that the dimension of design variables is lager than the number of response function. An adjoint method is required to compute adjoint variables from the simultaneous linear system equation, the so-called adjoint equation, requiring only the eigenvalue and its associated eigenvectors for mode being differentiated. This method has been extended to the repeated eigenvalue problem. In this paper, we propose an adjoint method for deign sensitivity analysis of damped vibratory systems with distinct eigenvalues.

• The Journal of Information Systems
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• v.18 no.3
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• pp.375-399
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• 2009

In this study, we propose a integrated model of logistic regression, artificial neural networks, support vector machines(SVM), with case-based reasoning(CBR). To predict respondents in the direct marketing is the binary classification problem as like bankruptcy prediction, IDS, churn management and so on. To solve the binary problems, we employed logistic regression, artificial neural networks, SVM. and CBR. CBR is a problem-solving technique and shows significant promise for improving the effectiveness of complex and unstructured decision making, and we can obtain excellent results through CBR in this study. Experimental results show that the classification accuracy of integration model using CBR is superior to logistic regression, artificial neural networks and SVM. When we apply the customer response model to predict respondents in the direct marketing, we have to consider from the view point of profit/cost about the misclassification.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.778-783
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• 2003

The problem considered in this paper is about the collocation of sensor and actuator for the active control of sound and vibration. It is well-known that a point collocated sensor-actuator pair offers an unconditional stability with very high performance when it is used with a direct velocity feedback (DVFB) control, because the pair has strictly positive real (SPR) property. In order to utilize this SPR characteristics, a matched piezoelectric sensor and actuator pair is considered, but this pair suffers from the in-plane motion coupling problem with the out-of$.$plane motion due to the piezo sensor and actuator interaction. This coupling phnomenon limits the stability and performance of the matched pair with DVFB control. As a new alternative, a point sensor and piezoelectric actuator pair is also considered, which provides SPR property in all frequency range except at the first resonance in very low frequency. This non-SPR resonance could be minimized by applying a phase lag compensator.