• Title/Summary/Keyword: difference vector

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New Data Extraction Method using the Difference in Speaker Recognition (화자인식에서 차분을 이용한 새로운 데이터 추출 방법)

  • Seo, Chang-Woo;Ko, Hee-Ae;Lim, Yong-Hwan;Choi, Min-Jung;Lee, Youn-Jeong
    • Speech Sciences
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    • v.15 no.3
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    • pp.7-15
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    • 2008
  • This paper proposes the method to extract new feature vectors using the difference between the cepstrum for static characteristics and delta cepstrum for dynamic characteristics in speaker recognition (SR). The difference vector (DV) which it proposes from this paper is containing the static and the dynamic characteristics simultaneously at the intermediate characteristic vector which uses the deference between the static and the dynamic characteristics and as the characteristic vector which is new there is a possibility of doing. Compared to the conventional method, the proposed method can achieve new feature vector without increasing of new parameter, but only need the calculation process for the difference between the cepstrum and delta cepstrum. Experimental results show that the proposed method has a good performance more than 2.03%, on average, compared with conventional method in speaker identification (SI).

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A Displacement Vector Estimation and Moving Object Extraction Using Difference Picture (Difference Picture를 이용한 이동벡터의 추정과 이동물체의 추출)

  • 장순화;김종대;김성대;김재균
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.7
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    • pp.807-818
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    • 1988
  • This paper proposes new algorithms for the estimation of displacement vector and moving object extraction using difference picture. First, the relations between the boundary of moving objects in two consecutive image and the boundary of difference picture regions are analyzed, then displacement vector estimation algorithm is proposed. Using the estimated displacement vector, moving objects are directly extracted from difference picture. Since the proposed algorithms do not process gray-valued image, they have a short processing time and are suitable to real time processing. From the experimental results, we observed that, if difference picture is wel extracted, the proposecd algorithms work well even in the circumstances of complex background, fast or slow motion, rotation etc., including occlusion where is not moving area.

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APPROXIMATE TANGENT VECTOR AND GEOMETRIC CUBIC HERMITE INTERPOLATION

  • Jeon, Myung-Jin
    • Journal of applied mathematics & informatics
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    • v.20 no.1_2
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    • pp.575-584
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    • 2006
  • In this paper we introduce a discrete tangent vector of a polygon defined on each vertex by a linear combination of forward difference and backward difference, and show that if the polygon is originated from a smooth curve then direction of the discrete tangent vector is a second order approximation of the direction of the tangent vector of the original curve. Using this discrete tangent vector, we also introduced the geometric cubic Hermite interpolation of a polygon with controlled initial and terminal speed of the curve segments proportional to the edge length. In this case the whole interpolation is $C^1$. Experiments suggest that about $90\%$ of the edge length is the best fit for the initial and terminal speeds.

Concept Drift Based on CNN Probability Vector in Data Stream Environment

  • Kim, Tae Yeun;Bae, Sang Hyun
    • Journal of Integrative Natural Science
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    • v.13 no.4
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    • pp.147-151
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    • 2020
  • In this paper, we propose a method to detect concept drift by applying Convolutional Neural Network (CNN) in a data stream environment. Since the conventional method compares only the final output value of the CNN and detects it as a concept drift if there is a difference, there is a problem in that the actual input value of the data stream reacts sensitively even if there is no significant difference and is incorrectly detected as a concept drift. Therefore, in this paper, in order to reduce such errors, not only the output value of CNN but also the probability vector are used. First, the data entered into the data stream is patterned to learn from the neural network model, and the difference between the output value and probability vector of the current data and the historical data of these learned neural network models is compared to detect the concept drift. The proposed method confirmed that only CNN output values could be used to reduce detection errors compared to how concept drift were detected.

A transductive least squares support vector machine with the difference convex algorithm

  • Shim, Jooyong;Seok, Kyungha
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.2
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    • pp.455-464
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    • 2014
  • Unlabeled examples are easier and less expensive to obtain than labeled examples. Semisupervised approaches are used to utilize such examples in an eort to boost the predictive performance. This paper proposes a novel semisupervised classication method named transductive least squares support vector machine (TLS-SVM), which is based on the least squares support vector machine. The proposed method utilizes the dierence convex algorithm to derive nonconvex minimization solutions for the TLS-SVM. A generalized cross validation method is also developed to choose the hyperparameters that aect the performance of the TLS-SVM. The experimental results conrm the successful performance of the proposed TLS-SVM.

Efficient Rotor Fault Detection of Induction Motors Using Stator Current Spectrum Monitoring (고정자 전류 스펙트럼 모니터링을 이용한 효과적인 유도전동기 회전자 고장 걸출)

  • 정춘호;우혁재;송명현;강의성;김경민
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.6
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    • pp.873-878
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    • 2002
  • Stator current spectrum by the fast Fourier transform (FFT) of current signals has been widely used for fault detection in induction motors. In this paper, we propose efficient rotor fault detection of Induction motors using stator current spectrum monitoring. The proposed method utilizes the mean absolute difference (MAD) between a Predetermined reference vector and a feature vector extracted from the stator current spectrum. Our proposed approach requires a smaller amount of computations when compared to fault detection algorithms based on neural networks, since it uses simple MAD criterion to detect rotor faults related broken rotor bars. Experimental results show that our proposed method can successively detect the rotor fault of the induction motor.

Infrared Thermal Video Stabilization Performance Comparison (열화상 영상 안정화 성능 비교)

  • Park, Chan-hyeok;Kwon, Hyuk-shin;Kang, Seok-hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.101-104
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    • 2015
  • Motion vector is that comparing a frame between previous frame and current one about how much moved. Using this motion vector, if move the image object of current frame to former frame, it could be corrected to shake from hand and camera shaking. On this thesis, compared efficiency of block matching using SAD(Sum of Absolute Difference) equation as picking out the motion vector, matching using phase correlation, matching using feature point, block matching using bitplane.

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Efficient Coding of Motion Vector Predictor using Phased-in Code (Phased-in 코드를 이용한 움직임 벡터 예측기의 효율적인 부호화 방법)

  • Moon, Ji-Hee;Choi, Jung-Ah;Ho, Yo-Sung
    • Journal of Broadcast Engineering
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    • v.15 no.3
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    • pp.426-433
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    • 2010
  • The H.264/AVC video coding standard performs inter prediction using variable block sizes to improve coding efficiency. Since we predict not only the motion of homogeneous regions but also the motion of non-homogeneous regions accurately using variable block sizes, we can reduce residual information effectively. However, each motion vector should be transmitted to the decoder. In low bit rate environments, motion vector information takes approximately 40% of the total bitstream. Thus, motion vector competition was proposed to reduce the amount of motion vector information. Since the size of the motion vector difference is reduced by motion vector competition, it requires only a small number of bits for motion vector information. However, we need to send the corresponding index of the best motion vector predictor for decoding. In this paper, we propose a new codeword table based on the phased-in code to encode the index of motion vector predictor efficiently. Experimental results show that the proposed algorithm reduces the average bit rate by 7.24% for similar PSNR values, and it improves the average image quality by 0.36dB at similar bit rates.

Applications of Characteristic Boundary Conditions within CFDS Numerical Framework (CFDS기법에 연계된 특성경계조건에 응용성에 대한 소개)

  • Hong S. K.;Lee K. S.
    • Journal of computational fluids engineering
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    • v.5 no.1
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    • pp.43-59
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    • 2000
  • Characteristic boundary conditions are discussed in conjunction with a flux-difference splitting formulation as modified from Roe's linearization. Details of how one can implement the characteristic boundary conditions which are made compatible with the interior point formulation are described for different types of boundaries including subsonic outflow and adiabatic wall. The validity of boundary conditions are demonstrated through computation of transonic airfoil, supersonic ogive-cylinder, hypersonic cylinder, and S-duct internal flows. The computed wall pressure distributions are compared with published experimental and computed data. Objectives of this paper are thus to give insight of formulation procedure of a flux-difference splitting method and to pave ways for other users to adopt present boundary procedure on their numerical methods.

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Rotor Time Constant Compensation of Vector Controlled Induction Motor Using Stator Current and Flux Error (고정자 전류와 자속의 오차를 이용한 벡터제어 유도전동기의 회전자 시정수 보상)

  • 김우현;박철우;임성운;권우현
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.5
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    • pp.367-375
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    • 2000
  • It is proposed that the rotor time constant and inductance are compensated at the same time in the indirect vector control method of an induction motor. The proposed scheme compensates the rotor time constant using the difference between the Q-axis real stator current and estimated current that is calculated from the terminal voltage and current, and compensates inductance by using the difference between the D-axis real stator flux and estimated stator flux in the synchronous rotating reference frame. Although the rotor time constant and inductance vary at once, the proposed method compensates the rotor time constant and inductance with accuracy. In addition to, two variables can be compensated not only at the steady state condition, but also at the transient state, where the torque varies in a rectangular pulse waveform. Therefore, the performance of vector control is greatly improved as verified by experiment.

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