• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.42-49
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• 1997

A conventional adaptive noise canceller (ANC) using LMS algorithm suffers from the misadjustment of adaptive filter weights due to the gradient-estimate noise by input speech signal at steady state. In this paper, an ANC is proposed which uses the combination of VSLMS (variable step size LMS) and SA (sign algorithm) to improve steady state performance and convergence rate. SA algorithm is applied in speech region to prevent the weights from perturbing by output speech of ANC and VSLMS algorithm is applied to improve convergence rate and channel tracking ability in silence region and adaptive transient region. In compute rsimulation, the performance of the proposed VSLMS-SA combination algorithm is much better than LMS algorithm and the algorithm, recently proposed by greenberg, with adaptation step-size parameter determine dby sum method in convergence rate, channel tracking and steady state performance.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.110-112
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• 2007

Output voltage waves of a DC/AC inverter system are likely to be distorted if variable loads e.g. motors or rectifiers exist in the output terminal. This paper designs a disturbance observer-based PI controller for a single-phase inverter system that is robust against load changes. In this paper, we regard the output voltage changes due to various loads as disturbances of the control system, Then we design a disturbance observer for estimation of the disturbances caused by the load current and any other error sources (such as parameter uncertainties and model mismatches etc.). In order to test the performance of the proposed control law, simulation studies are carried out for a single-phase inverter system using SimPowerSystems of Matlab Simulink. Compared to a simple PI control, the disturbance observer-based controller shows enhanced performance in transient responses for step load changes.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.516-523
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• 2013

This paper investigates an improved stator flux linkage observer for sensorless permanent magnet synchronous motor (PMSM) drives using a voltage-based flux linkage model and an adaptive sliding mode variable structure. We propose a new observer design that employs an improved sliding mode reaching law to achieve better estimation accuracy. The design includes two models and two adaptive estimating laws, and we illustrate that the design is stable using the Popov hyper-stability theory. Simulation and experimental results demonstrate that the proposed estimator accurately calculates the speed, the stator flux linkage, and the resistance while overcoming the shortcomings of traditional estimators.

• Earthquakes and Structures
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• v.4 no.5
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• pp.509-525
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• 2013

In this paper, learning capabilities of two types of Arterial Neural Networks, namely hierarchical neural networks and Generalized Regression Neural Network were used in a two-stage approach to develop a method for generating spatial varying accelerograms from acceleration response spectra and a distance parameter in which generated accelerogram is desired. Data collected from closely spaced arrays of seismographs in SMART-1 array were used to train neural networks. The generated accelerograms from the proposed method can be used for multiple support excitations analysis of structures that their supports undergo different motions during an earthquake.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.8
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• pp.1035-1039
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• 2000

This study developed a Poisson generalized linear mixed model and a procedure to estimate genetic parameters for count traits. The method derived from a frequentist perspective was based on hierarchical likelihood, and the maximum adjusted profile hierarchical likelihood was employed to estimate dispersion parameters of genetic random effects. Current approach is a generalization of Henderson's method to non-normal data, and was applied to simulated data. Underestimation was observed in the genetic variance component estimates for the data simulated with large heritability by using the Poisson generalized linear mixed model and the corresponding maximum adjusted profile hierarchical likelihood. However, the current method fitted the data generated with small heritability better than those generated with large heritability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.395-398
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• 2001

In this paper, we consider to apply of 2-DOF (Degree of Freedom) PID controller at D.C servo motor system. Many control system use I-PD, PID control system but the position control system have difficulty in controling variable load and changing parameter. We propose neural network 2-DOF PID control system haying feature for removal disturbances and tracking function in the target value point. Experiment result for 2-DOF PID controller with neural network are illustrated.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.745-749
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• 2003

The iterative sliding mode observer is proposed to control sensorless PMSM(Permanent Magnet Synchronous Motor). Proposed sliding mode observer has the character which is robust to the disturbance and parameter variation. Low pass filter with the variable cutoff frequency is also proposed to compensate rotor angle, it is led to saving memory and minimizing operation time. Experimental results shows that the proposed sliding mode observer leads to the proper performance.

• Journal of Power Electronics
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• v.9 no.2
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• pp.207-214
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• 2009

This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.233-237
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• 2006

This study proposes an innovative measure for evaluating the performance of text clustering. In using K-means algorithm and Kohonen Networks for text clustering, the number clusters is fixed initially by configuring it as their parameter, while in using single pass algorithm for text clustering, the number of clusters is not predictable. Using labeled documents, the result of text clustering using K-means algorithm or Kohonen Network is able to be evaluated by setting the number of clusters as the number of the given target categories, mapping each cluster to a target category, and using the evaluation measures of text. But in using single pass algorithm, if the number of clusters is different from the number of target categories, such measures are useless for evaluating the result of text clustering. This study proposes an evaluation measure of text clustering based on intra-cluster similarity and inter-cluster similarity, what is called CI (Clustering Index) in this article.

• Annual Conference of KIPS
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• 2001.04b
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• pp.1161-1164
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• 2001

본 논문에서는 무선 ATM 망에서 VBR(Variable Bit Rate) 트래픽의 QoS(quality of Service)를 보장하고 무선 채널의 효율성을 극대화 할 수 있는 새로운 적응적 슬롯 할당 알고리즘인 In-VDSA를 제안한다. 제안된 알고리즘에서는 ATM 셀 헤더 부분의 GFC(Generic Flow Field) 필드 상에 단말기의 버퍼 상태를 부호화하여 piggybacking하는 방식을 채택하였으며 다음 프레임에 할당할 슬롯의 개수를 기존의 다른 방식과는 달리 유동적으로 조절하여 할당함으로써 단말기의 셀 손실이나 지연에 대한 QoS를 보장하고 채널 이용 효율을 높일 수 있었다. 제안된 알고리즘은 BONeS tool을 이용한 시뮬레이션을 통하여 기존의 방식과 비교 분석한 결과 그 정당성을 확인하였다.