• 제목/요약/키워드: Vector Algorithm

검색결과 3,104건 처리시간 0.037초

분광 유사도 커널을 이용한 하이퍼스펙트럴 영상의 Support Vector Machine(SVM) 분류 (Support Vector Machine Classification of Hyperspectral Image using Spectral Similarity Kernel)

  • 최재완;변영기;김용일;유기윤
    • 대한공간정보학회지
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    • 제14권4호통권38호
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    • pp.71-77
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    • 2006
  • 통계학습이론에 기반하고 있는 Support Vector Machine(SVM)은 구조적 위험 최소화원리를 바탕으로 하는 학습 알고리즘이다. 일반적으로SVM은 비선형 경계를 결정하고 자료를 분류하기 위해서 커널(kernel)을 사용한다. 그러나 기존의 커널들은 두 벡터간의 내적이나 거리차를 이용하여 유사도를 측정하기 때문에 하이퍼스펙트럴 영상분류에 효과적으로 적용될 수 없다. 본 논문에서는 이를 해결하기 위해서 분광유사도커널(Spectral similarity kernel)을 제안한다. 분광유사도 커널은 두 벡터의 거리차와 각 차이를 모두 계산하는 지역적 커널로 하이퍼스펙트럴 영상의 분광특성을 효과적으로 고려할 수 있다. 이를 검증하기 위해서 Hyperion 영상에 polynomial kernel, RBF kernel을 사용한 SVM 분류기와 분광유사도 커널을 사용한 SVM 분류기를 적용하여 토지피복분류를 시행하였다. 분류결과를 통해서 분광유사도 커널을 사용한 SVM 분류기가 정량적, 공간적으로 가장 우수한 결과를 보임을 확인하였다.

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Sensorless Control of a PMSM at Low Speeds using High Frequency Voltage Injection

  • Yoon Seok-Chae;Kim Jang-Mok
    • Journal of Power Electronics
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    • 제5권1호
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    • pp.11-19
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    • 2005
  • This paper describes the two control techniques to perform the sensorless vector control of a PMSM by injecting the high frequency voltage to the stator terminal. The first technique is the estimation algorithm of the initial rotor position. A PMSM possesses the saliency which produces the ellipse of the stator current when the high frequency voltage is injected into the motor terminal. The major axis angle of the current ellipse gives the rotor position information at a standstill. The second control technique is a sensorless control algorithm that injects the high frequency voltage to the stator terminal in order to estimate the rotor position and speed. The rotor position and speed for sensorless vector control is calculated by appropriate signal processing to extract the position information from the stator current at low speeds or standstill. The proposed sensorless algorithm using the double-band hysteresis controller exhibits excellent reference tracking and increased robustness. Experimental results are presented to verify the feasibility of the proposed control schemes. Speed, position estimation and vector control were carried out on the floating point processor TMS320VC33.

A Voice Controlled Service Robot Using Support Vector Machine

  • Kim, Seong-Rock;Park, Jae-Suk;Park, Ju-Hyun;Lee, Suk-Gyu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1413-1415
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    • 2004
  • This paper proposes a SVM(Support Vector Machine) training algorithm to control a service robot with voice command. The service robot with a stereo vision system and dual manipulators of four degrees of freedom implements a User-Dependent Voice Control System. The training of SVM algorithm that is one of the statistical learning theories leads to a QP(quadratic programming) problem. In this paper, we present an efficient SVM speech recognition scheme especially based on less learning data comparing with conventional approaches. SVM discriminator decides rejection or acceptance of user's extracted voice features by the MFCC(Mel Frequency Cepstrum Coefficient). Among several SVM kernels, the exponential RBF function gives the best classification and the accurate user recognition. The numerical simulation and the experiment verified the usefulness of the proposed algorithm.

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Vector Quantization for Medical Image Compression Based on DCT and Fuzzy C-Means

  • Supot, Sookpotharom;Nopparat, Rantsaena;Surapan, Airphaiboon;Manas, Sangworasil
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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    • pp.285-288
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    • 2002
  • Compression of magnetic resonance images (MRI) has proved to be more difficult than other medical imaging modalities. In an average sized hospital, many tora bytes of digital imaging data (MRI) are generated every year, almost all of which has to be kept. The medical image compression is currently being performed by using different algorithms. In this paper, Fuzzy C-Means (FCM) algorithm is used for the Vector Quantization (VQ). First, a digital image is divided into subblocks of fixed size, which consists of 4${\times}$4 blocks of pixels. By performing 2-D Discrete Cosine Transform (DCT), we select six DCT coefficients to form the feature vector. And using FCM algorithm in constructing the VQ codebook. By doing so, the algorithm can make good time quality, and reduce the processing time while constructing the VQ codebook.

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Lifting Scheme과 PVQ를 이용한 영상압축 기법 (An Image Compression Technique with Lifting Scheme and PVQ)

  • 정전대;김학렬;신재호
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1996년도 학술대회
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    • pp.159-163
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    • 1996
  • In this paper, a new image compression technique, which uses lifting scheme and pyramid vector quantization, is proposed. Lifting scheme is a new technique to generate wavelets and to perform wavelet transform, and pyramid vector quantization is a kind of vector quantization which dose not have codebook neither codebook generation algorithm. For the purpose of realizing more compression rate, an arithmetic entropy coder is used. Proposed algorithm is compared with other wavelet based image coder and with JPEG which uses DCT and adaptive Huffman entropy coder. Simulation results showed that the performance of proposed algorithm is much better than that of others in point of PSNR and bpp.

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고음질을 갖는 음색변경에 관한 연구 (A Study on the Voice Conversion Algorithm with High Quality)

  • 박형빈;배명진
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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    • pp.157-160
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    • 2000
  • In the generally a voice conversion has used VQ(Vector Quantization) for partitioning the spectral feature and has performed by adding an appropriate offset vector to the source speaker's spectral vector. But there is not represented the target speaker's various characteristics because of discrete characteristics of transformed parameter. In this paper, these problems are solved by using the LMR(Linear Multivariate Regression) instead of the mapping codebook which is determined to the relationship of source and target speaker vocal tract characteristics. Also we propose the method for solved the discontinuity which is caused by applying to time aligned parameters using Dynamic Time Warping the time or pitch-scale modified speech. In our proposed algorithm for overcoming the transitional discontinuities, first of all, we don't change time or pitch scale and by using the LMR change a speaker's vocal tract characteristics in speech with non-modified time or pitch. Compared to existed methods based on VQ and LMR, we have much better voice quality in the result of the proposed algorithm.

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회전자 시정수 보상 알고리즘을 갖는 유도전동기의 벡터제어 (Vector Control of Induction Motors with Compensation Algorithm of Rotor Time Constant)

  • 김종국;이득기;정종진;김홍근
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 하계학술대회 논문집 F
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    • pp.1964-1967
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    • 1997
  • The rotor time constant variation has a large effect on the vector controlled system of induction motor. In this paper, the algorithm which compensate the misalignment of the rotor flux vector as an error caused by incorrect rotor time constant are presented. The simulations show that the proposed algorithm suitably compensates the rotor time constant.

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제어알고리즘 개선을 위한 3차원 반송 시스템 선형유도전동기의 동특성 해석 (Dynamic Characteristics Analysis of 3D Conveyor System Linear Induction Motor for Control Algorithm Developments)

  • 전수진;이중호
    • 전기학회논문지
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    • 제56권3호
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    • pp.514-518
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    • 2007
  • It is necessary to modify the state-of-the-art of speed control theory because of the phase asymmetry in the Linear Induction Motor (LIM)and for the constant speed control of mover using single vector control inverter system, it is important that primary stack is located in appropriated intervals in the 3D conveyer system using LIM. The dynamic characteristic analysis method of the vector controlled LIM using coupled FEM and control algorithm taking into account the movement is proposed. The focus of this paper is the analysis relative to selecting primary stack intervals in order to constant speed control in the 3D conveyer system using LIM.

함수근사를 위한 서포트 벡터 기계의 커널 애더트론 알고리즘 (Kernel Adatron Algorithm of Support Vector Machine for Function Approximation)

  • 석경하;황창하
    • 한국정보처리학회논문지
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    • 제7권6호
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    • pp.1867-1873
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    • 2000
  • 함수근사는 과학과 고학부야에서 공범위하게 응용된다. 시포트 벡터 기계(support vector machine, SVM)는 원래 분류를 위해 계안되어져 문자인식, 얼굴인식 등의 응용분야에서 좋은 결과를 보여주고 있다. 최근 SVM이론 함수근사로 확장되어 많이 활용되려 하고 있다. 그러나 함수근사를 위한 SVM 알고리즘은 QP(quadratic proramming)문제와 관련되어있어 계산에 시간이 걸리며 QP를 위한 패키지가 있어야 한다. 본 논문에서는 함수근사를 위해 커널-애더트론 알고리즘을 이용한 SVM을 제안하고 QP를 이용한 SVM과 성능을 비교하고자 한다.

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