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Thyristor의 비대칭 트리거에 의한 부하의 정상상태 해석
이쾌희 울산대학교 1977 연구논문집 Vol.8 No.1
쌍방향성 싸이리스티의 비대칭 트리거에 의한 부하의 특성을 해석하고 부하에 의한 부하의 특성을 해석하고 부하의 역률에 대하여 알아보았다. 또한 전력, 의형률 그리고 기본파의 역률을 계산했다. The load wave forms produced by asymmetrical triggering of an inverse-parallel connected pair of thyristors are analyzed. The power factor of the circuits is studied and its relationship to power, distortion factor and fundamental power factor is given.
Runge Kutta Method를 이용한 평가지표에 관한 연구
이쾌희,정천석 울산대학교 1976 연구논문집 Vol.7 No.1
본 논문에서는Runge Kutta Method를 사용하여 평가지표를 계산하고 또 시스템을 설계하는데 있어서 그 값을 최소화 시키는 시스템의 Parameter를 결정하는데 필요한 프로그래밍을 개발하였다. 3계 시스템에 한해서 결과를 냈지만 다른 경우에도 대동소이하게 이용할 수 있다. This study involves the computation result for the performance criteria by Runge Kutta Method and the programming of the determination of parameters which minimize the performance criteria, which is essential for the system design. This paper covers only third order systems but it will be applicable for other systems.
성홍석,이쾌희 대한전자공학회 1997 電子工學會論文誌, S Vol.s34 No.9
In this paper, we describe the algorithm which controls an unknown nonlinear system with disturbance a using multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate an unknown nonlinear system by using of multilayer neural netowrk. WE include a disturbance among the modelling error, and the weight-update rule of multilayer neural network is derived to satisfy Laypunov stability. The whole control system constitutes controller using the feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.
조음 특성과 음소 대표 구간을 이용한 우리말 파열음의 인식
박찬응,이쾌희 대한전자공학회 1997 電子工學會論文誌, S Vol.s34 No.4
Korean unvoiced phonemes consist of nonstationary parts comparing that the vowels and nasal consonants consist of quasi-stationary part. And some phonemes, which have smae point of articulation but differnt manner of articulation, has similar characteristics, so it makes to be hard to distinguish each other. A new method usin gchanges and characteristics of acoustic properties of these phonemes to improve recognition rate are proposed. And because these changes and cahracteristics evidently occur in continuous speech except some unvoiced consonants are articulated as voiced phoneme in case to be used as an midial between voiced phonemes, this method can be applied easily. The features of the frames extracted to represent each phonemes are used asinputs to the hierarchical neural network. And with these results final decision for phoneme recognition is made thorugh post processing which the new method is applied to. Through the experimental recognition results for 9 unvoiced consonants which belong to bilabial, alveolar, and velar phoneme series, 89.4% recognition rate to distinguish in same phoneme series is obtained, and 85.6% recognition rate is obtained in case of including cistinguishing phoneme series.