http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
이권현,조경재 전남도립대학교 1999 전남도립대학교 논문집 Vol.S No.-
We introduce the systematization design method using similarity theory. The design method can make us predict the characteristic experiment for the magnitude we desire as the expression equation applied continuously. We can induce the design sample the users demand with the verification of the data on optimum design previously. Therefore, in case of designing and developing the products, systematization design method is very useful for the standardization of the developed goods, compatability, the reduction of construction time and price. In this paper, we present the analogical, algorithms of systematization design using similarity theory, design factors and processing method of the restriction factors. Also, we analyze the output voltage ìn terms of input voltage and displacement as choosing a differential transformer as the model.
이권현 한국통신학회 1991 韓國通信學會論文誌 Vol.16 No.4
본 논문에서는 전화번호 서비스시 사용되고 있는 영(zero)에서 일까지의 2종류의 숫자음(한글발음의 셈수와 한자발음의 읽음수) 22개에 대하여 신경회로망을 이용한 음성인식 실험의 결과와 학습과정에서 나타난 제 현상에 관해 논하였다. 신경회로망은 입력단과 출력단만을 갖는 2단구조와 한 개의 은익단을 갖는 3단구조의 회로망으로 은익단의 뉴론(Neuron) 수를 11, 12 및 44개로 가변해 가면서 BP(Back-Propagation) 알고리즘에 의하여 학습하였고 학습과정에서는 학습팩터(Learning factor), 학습방법(예로써 Random or Cycle), 모멘텀(Momentum)등을 조정해 가면서 최적의 학습과정을 찾고자 하였다. 실험결과 2단구조에 의한 화자독립의 경우 최고 96%의 인식율을 나타냈고 학습과정이 너무 많을 경우 오히려 인식율이 낮아졌으며 이 현상은 3단구조의 회로망에서 더욱 두드러지게 나타났다. A speech recognition system based on a neural network, which can be used for telephon number services was tested. Because in Korea two different cardinal number systems, a koreanic one and a sinokoreanic one, are in use, it is necessary that the used systems is able to recognize 22 discret words. The structure of the neural network used had two layers, also a structure with 3 layers, one hidden layreformed of each 11, 22 and 44 hidden units was tested. During the learning phase of the system the so called BP-algorithm (back propagation) was applied. The process of learning can e influenced by using a different learning factor and also by the method of learning(for instance random or cycle). The optimal rate of speaker independent recognition by using a 2 layer neural network was 96%. A drop of recognition was observed by overtraining. This phenomen appeared more clearly if a 3 layer neural network was used. These phenomens are described in this paper in more detail. Especially the influence of the construction of the neural network and the several states during the learning phase are examined.
이권현,강희조 한국통신학회 1992 韓國通信學會論文誌 Vol.17 No.1
전동기 회전시 발생되는 소음이 전동기 구조상의 소손부분 및 정도에 따라 서로 다른 소음의 특징을 갖는다는 점을 고려하여 신경회로망을 이용한 시그널(소음)인식 시스템으로써 전동기의 고장부분 탐지에 적용하였다. 적용된 신경회로망은 역전파(back-propagation)알고리즘을 써서 학습하였고 2개의 은역층을 갖는 4단 신경회로망으로 구성 되었다. 실혐 결과 전동기의 구조와 출력이 거의 일치하는 경우에는 고정 부분에 대한 항상 바른 판정을 내릴 수 있었으나 출력은 유사하더라도 전동기의 구조가 상이한 경우나 전동기 제작회사가 다른 경우에는 부정확한 판정으로 나타난다. Subject of this work is the application of neural networks for the signal(motor noise)recognition systems which detects motor failures and employs different signal(noise). Charaoteristics that re-sult from damaghe part and measure of motor construction during working. The four layers neural networks is applied to this examination. And consists of one input layer, two hidden layers, and one output layer, and learns by the back propagation algorithm.The results of this examination show that it the construction and the output power of the testmotor and learning motor are compatible, the damaged part of the testmotor are detected correctly in the system on the other hand, if the motors have different constrcotion but similar output power each other, mislesding results are obtained in this system.
李權鉉,趙慶宰 東新大學校 工業技術硏究所 1997 工業技術硏究 Vol.3 No.-
This paper presents the system demonstrator for an optical fiber sensor system developed as a technological evaluator suitable for generic sensing applications. The new type of fiber-optic sensor employed a diaphragm displacement transforms pressure into optical intensity. From this sensing technique, we can know the variation of source intensity, the loss of a optical fiber, and the reflectivity of the diaphragm surface. Experimental results are applied to the low-pressure transducer suitable for measuring miniature pressure.