• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.347-350
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• 융합신호처리학회논문지
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• 제2권2호
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• pp.111-118
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• 2001

본 연구에서는 패턴 인식용 다층 퍼셉트론 신경망을 순수 디지털 논리회로 모델로 구현할 수 있도록 새로운 논리뉴런의 구조, 디지털 정형 다층논리신경망 구조, 그리고 패턴인식의 응용을 위한 다단 다층논리 신경망 구조를 제안하고, 또한 제안된 구조는 매우 단순하면서도 효과적인 증가적인 가법적(Incremental Additive) 학습알고리즘이 존재함을 보였다.

• International Journal of Korean Welding Society
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• 제1권1호
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• pp.7-12
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• 2001

Real time monitoring has become critical as the use of laser welding increases. Plasma and spatter are measured and used as the signal for estimating weld quality. The estimating algorithm was made using the fuzzy pattern recognition with the area of data that is beyond the tolerance boundary. Also, an algorithm that detects the spatter and the localized defect was created in order to kd the partially produced pit and the sudden loss of weld penetration. These algorithms were used in quality monitoring of the $CO_2$ laser tailored blank weld. Statistical program that can display the laser weld quality result and the signal transition was made for the first stage of the remote control system.

• 한국정밀공학회지
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• 제17권7호
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• pp.98-105
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• 2000

In this study, we developed rotating machine vibration condition monitoring system based upon Windows NT and DSP Board. Developed system includes signal analysis module, trend monitoring and simple diagnosis using threshold value. Trend analysis and report generation are offered with database management tool which was developed in MS-ACCESS environment. Post-processor, based upon Matlab, is developed for vibration signal analysis and fault detection using statistical pattern recognition scheme based upon Bayes discrimination rule and neural networks. Concerning to Bayes discrimination rule, the developed system contains the linear discrimination rule with common covariance matrices and the quadratic discrimination rule under different covariance matrices. Also the system contains k-nearest neighbor method to directly estimate a posterior probability of each class. The result of case studies with the data acquired from Pyung-tak LNG pump and experimental setup show that the system developed in this research is very effective and useful.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2009년도 춘계학술발표회 논문집
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• pp.65-73
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• 2009

The terrestrial laser scanner measures the signal delay time of electronic circuit in EDM(Electronic Distance Measurement) Module for distance measurement. To measure signal delay time precisely, transmitting laser beam of terrestrial laser scanner is divided optically. Therefore, 10% of the laser beam power is entered into the electronic circuit and the others go out through lens. But, measure of delay time is severe in the laser scanner system that the laser beam power is changed dynamically by reflectance of a object, because characters like gain of electronic circuit involving APD(Avalanche Photo Diode) and so on are changed by incident laser beam. Therefore, we adapt ND(Neutral Density) filter that has grid pattern to the laser scanner system to keep constant the incident laser beam power. In this paper, we propose the simulation program for efficient design of ND filter pattern. Finally, to affirm simulation program, we conduct the experimental test of simulated ND filter that has linearly transmittance change, and we consider the experiment result.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2018년도 전력전자학술대회
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• pp.332-333
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• 2018

This paper presents an advanced abnormal over-current protection with $SuperFET^{(R)}$ 800V MOSFET in Flyback converter. In advanced abnormal over-current protection, digital pattern generator is proposed to detect a steep di/dt current condition when secondary rectifier diode or the transformer is shorted. If current sensing signal is larger than current limit during consecutive switching cycle, Gate signal will be stopped for 7 internal switching periods. If the abnormal over-current maintains pattern, the controller goes into protection mode. The Advanced over-current protection has been implemented in a 0.35um BCDMOS process (ON Semiconductor process).

• 한국정보통신학회논문지
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• 제3권3호
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• pp.627-638
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• 1999

In this paper, the system with an artificial intelligent that is able itself to adjust the perimeter condition of the plant is presented. The proposed intelligent system is composed of two learning vector quantization(LVQ) networks, which are used mostly in the field of the pattern recognition and signal processing. From the external condition of the plant, the first LVQ network recognizes the pattern of the sensed signal and the second LVQ network judges synthetically user's characteristics and performs learning. The controller controls the plant using the reference value, which is the output value of the synthetic judgement part. In order to verify the usefulness of the proposed method, we simulated the two LVQs are implemented for the artificial intelligent illuminator as well as being carried out computer simulations. We implemented the proposed artificial intelligent illuminator and perform the experiment.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2448-2450
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• 1998

For the exact classification of the arm motion this paper proposes EMG pattern recognition method with neural network. For this autoregressive coefficient, linear cepstrum coefficient, and adaptive cepstrum coefficient are selected for the feature parameter of EMG signal, and they are extracted from time series EMG signal. For the function recognition of the feature parameter a radial basis function network, a field of neural network is designed. For the improvement of recognition rate, a number of radial basis function network are combined in parallel, comparing with a backpropagation neural network an existing method.

• 대한전자공학회논문지
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• 제24권5호
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• pp.880-886
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• 1987

This paper proposes a new pattern recognition system using Radon transform and analyzes the performances of the system for given input patterns. The proposed system uses many optical parts in order to utilize the high speed characteristics of light and processes a signal easily by transforming 2-D image into a 1-D signal to increase flexibility. The squared Mahalanobis distance obtained from means and standard deviations of the features for the given input patterns is used for discrimination. As a result, this system represents a better recognition rate than any other systems using the same input patterns.

• 비파괴검사학회지
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• 제12권2호
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• pp.21-29
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• 1992

Acceleration signal characteristics of a steel plate, impacted by steel balls, were studied in an attempt to apply the experimental results to the impact location and mass estimation of metallic loose parts in the cooling system of nuclear power plants. Experimental results show that the variation of maximum acceleration amplitude and impact contact time due to the change of ball mass and impact velocity can be well explained by the Hertz impact theory. The frequency spectral pattern shifted slightly in spite of the increase of impact velocity and impact location. Ball mass, however, strongly affected the frequency spectral pattern. Hence the frequency spectrum can be used for estimation of the mass of unknown loose parts in the cooling system.