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강윤정,이재일,배진호,이종현,Kang, Youn Joung,Lee, Jaeil,Bae, Jinho,Lee, Chong Hyun 대한전자공학회 2013 전자공학회논문지 Vol.50 No.6
본 논문에서는 정지하고 있는 배경에서 움직이는 목표물을 식별하기 위해 PDR(pulse doppler radar)을 이용하여 수집한 복소수 신호를 처리하는 복소수 SVM(support vector machine)을 제안한다. SVM은 패턴인식 분야에서 널리 이용되나 분류에 이용되는 특징이 대부분 실수 데이터이다. 제안된 복소수 SVM은 실수 데이터, 허수 데이터 정보와 실수부와 허수부 사이의 교차 정보를 모두 이용하여 이동하는 목표물의 분류를 수행한다. 복소수 SVM을 설계하기 위해 최적화 조건 적용 시 실수축과 허수축에 대한 슬랙변수를 고려하였고, 복소수 데이터에 대한 KKT(Karush-Kuhn-Tucker) 조건을 이용하였다. 또한 복소수 거리를 이용한 RBF(radial basis function)를 커널함수로 적용하였다. 제안된 복소수 SVM의 성능을 평가하기 위해 PDR 센서로 수집된 복소 데이터를 기존의 SVM과 복소수 SVM을 이용하여 분류한 결과 기존의 SVM에 비해 복소수 SVM의 식별결과가 개와 사람 각각 8%, 10% 향상되었다. In this paper, we propose a complex-valued support vector machine (SVM) classifier which process the complex valued signal measured by pulse doppler radar (PDR) to identify moving targets from the background. SVM is widely applied in the field of pattern recognition, but features which used to classify are almost real valued data. Proposed complex-valued SVM can classify the moving target using real valued data, imaginary valued data, and cross-information data. To design complex-valued SVM, we consider slack variables of real and complex axis, and use the KKT (Karush-Kuhn-Tucker) conditions for complex data. Also we apply radial basis function (RBF) as a kernel function which use a distance of complex values. To evaluate the performance of the complex-valued SVM, complex valued data from PDR were classified using real-valued SVM and complex-valued SVM. The proposed complex-valued SVM classification was improved compared to real-valued SVM for dog and human, respectively 8%, 10%, have been improved.
Footstep Detection and Classification Algorithms based Seismic Sensor
강윤정,이재일,배진호,이종현,Kang, Youn Joung,Lee, Jaeil,Bea, Jinho,Lee, Chong Hyun The Institute of Electronics and Information Engin 2015 전자공학회논문지 Vol.52 No.1
본 논문에서는 적응형 걸음걸이 검출 알고리즘과 검출된 신호로부터 단일 발자국의 움직임을 분류하는 알고리즘을 제안한다. 제안된 단일 발자국 기반 알고리즘은 기존의 연속된 발자국 신호를 이용한 분류 방식이 아니기 때문에 전체적인 움직임뿐만 아니라 개별적이고 불규칙한 움직임도 검출 및 분류 가능하다. 분류를 위해 사용된 특징벡터는 발자국 신호의 푸리에 스펙트럼, CWT의 스펙트럼, AR 모델링 스펙트럼과 AR 스펙트로그램 영상으로부터 얻어진 벡터이다. SVM을 이용하여 단일 발자국의 움직임을 분류한 결과 AR 스펙트로그램으로 얻어진 특징벡터를 사용할 경우 90% 이상 분류 성능을 얻었다. In this paper, we propose an adaptive detection algorithm of footstep and a classification algorithm for activities of the detected footstep. The proposed algorithm can detect and classify whole movement as well as individual and irregular activities, since it does not use continuous footstep signals which are used by most previous research. For classifying movement, we use feature vectors obtained from frequency spectrum from FFT, CWT, AR model and image of AR spectrogram. With SVM classifier, we obtain classification accuracy of single footstep activities over 90% when feature vectors using AR spectrogram image are used.
袴의 發生 및 形制 고찰 : 古代 東北亞細亞를 중심으로
윤영애,강윤정 진주여자전문대학 1997 論文集 Vol.20 No.-
In the Northeast Asia the Koh was in the class of the Northern Chinese garment, and was used widely by the horse riding Scythians who moved widely from the Eurasian inland to Japan. The oldest original which could reflect the type of the Northern clothes was a pair of trousers discovered in the Huns remains of Noin Ula. This showed the exact form of hunting clothes and had a similar form with the Korean female trousers. Since the same form of trousers drawn on the wall painting of which was excavated 4-5th century ancient Koguryo tomb was the same form, the trousers of Noin Ula seemed to be the original form of Koh in the Northeast Asia. The Chinese trousers were influenced by the Huns, the Northern clothes of the Scythian culture, and similar to the Korean clothes. Korean was a race bared from the Eastern foreign group. It was obvious that the clothes was Baji-Jeogori, the garment of the Northern people. This had the same form of the Scythian dress and ornaments which was excavated from the Mongolian Noin Ula. The ancient Japanese clothes were influenced by the Southern factor but not the form of the Koh. As the Korean people group was moving towards Japan and conquer the Japanese in the 4-5th century, however, North Altaic culture was formed and at the same time the clothes were also developed. The most influenced clothes at this time were those of Baekge and the trousers form called Euigon became the main form. Because of the climatic regional factor, it was tied not at the ankle but under the knee.