Earticle

In this paper, a denoising algorithm and simulation experiments of algorithm based on wavelet transform and support vector machine (SVM) image is proposed, a new method is adopted in the selection of characteristic vector of support vector machine, based on training of support vector machine, the support vector machine model is used to distinguish between noise and the original image, to achieve the effect of denoising. The experimental results show that the method can well remove the noise, and can save some important details of images, compared with other denoising method based on wavelet transform, it has a good advantage.

Main interest of the present paper is to investigate the criticality of characteristic vector fields on almost cosymplectic manifolds. Killing critical characteristic vector fields are absolute minima. This paper contains some examples of non-Killing critical characteristic vector fields.

In this paper we study CR-submanifolds of maximal CR-dimension by investigating extrinsic behaviors of integral curves of characteristic vector field on them. Also we consider the notion of ruled CR-submanifold of maximal CR-dimension which is a generalization of that of ruled real hypersurface and find some characterizations of ruled CR-submanifold of maximal CR-dimension concerning extrinsic shapes of integral curves of the characteristic vector field and those of CR-Frenet curves.

An almost contact metric manifold is called a quasi contact metric manifold if the corresponding almost Hermitian cone is a quasi Kähler manifold, which was introduced by Y. Tashiro [9] as a contact O*-manifold. In this paper, we show that a quasi contact metric manifold with Killing characteristic vector field is a K-contact manifold. This provides an extension of the definition of K-contact manifold.

This paper presents magnetic field analysis technology that uses a vector magnetic characteristic. Recently the magnetic material was found to be measurable using the vector quantity technique. Therefore considering the anisotropy of the magnetic material in the vector field analysis is necessary. The magnetic field analysis method, which is considered the anisotropy by combining the finite element method with the E&$S^2$ (Enokizono, Soda, and Shimoji) modeling, is applied to a permanent magnet motor model.

This study examines the K-pop ‘concept’ from a management perspective, viewing it not as a cultural or artistic perspective with categoricalism but as a strategic approach tied to resource allocation, marketing, and sales. Unlike the previous research that asked how concepts change, this study focuses on why they change through arguing the change was analyzed as the variability, which is intentional and based on fandom vector, of K-pop concept from the changeability of it in the previous study. To do this, this study employs the causal model and feedback model with mathematical logic. And through cases of Brown Eyed Girls and PSY, it illustrates how deliberate concept shifts can boost concept effect and consumers’ engagement in the real market.

본 논문에서는 음성의 특징벡터를 추출하여 음성인식을 위한 인식 알고리즘을 제안한다. 본 논문에서 제안하는 방법은 사람의 음성을 정규화하여 시간지연신경회로망을 사용하여 음성인식을 하는 인식 알고리즘이다. 본 논문에서는 시간지연신경회로망을 이용하여 입력되는 음성정보를 일정시간 동안 학습시킨 후에 새로이 입력되는 정보를 인식하는 수법이다. 본 실험에서는 음성인식률에 의하여 본 알고리즘의 유효성을 확인한다.

본 연구에서는 기존 방법과는 달리, 음성의 특징추출의 한 방법으로 음성의 통계적인 특성들을 고려하여 입력 공간 내에서 변동량이 가장 많은 방향으로 주축을 발견한 후, 그 정보를 이용하여 데이터의 중복성을 제거하는 주성분 해석기법을 사용하여 음성의 특징을 추출하는 방법을 제안한다. 본 연구에서의 숫자음 인식실험 결과가 기존 멜-켑스트럼을 사용하였을 때와 0.5%의 인식률 차의 유사 인식률을 나타내었다. 한편, 데이터의 통계적 특성을 이용한 최적의 기저벡터를 이용하여 단어나 문장 인식에 적용한다면 보다 더 개선된 인식률을 얻으리라 기대하고 있다.

The new method of characteristic extraction is proposed, considering the statistic characteristic of human speech, unlike the conventional methods of the traditional speech characteristic extraction. PCA(Principal Component Analysis) is applied to new this method. Then, the new method is applied to real speech recognition to assess performance. When results of the number recognition in this research and the conventional Mel-cepstrum of speech characteristic parameter are compared, there is 0.5% difference of recognition rate. Better recognition rate is expected than word or sentence recognition in that less convergence time than the conventional method in extracting speech characteristic. Also, Better recognition rate is expected when the optimum vector is used by statistic characteristic of data.

본 논문에서는 원영상 영역내 포함된 우성의 에지에 대한 구체적 정보를 이용하기 위하여 Haar 웨이블릿을 이용한 에지영상 추출한다. 추출된 에지영상에 얼굴영역을 검출하기위해 이진화된 영상에 설정된 임계값을 통하여 얻은 이진영상으로부터 얼굴영역을 검출하기 위하여 얼굴의 일반적인 구조적 정보와 처리시간이 빠른 수평, 수직히스토그램 분석법을 이용하였다. 얼굴영역을 분리한 영상에 얼굴영역의 특징벡터를 구하기 위하여 26개의 특징벡터를 사용한 효율적인 고차 국소 자동 상관함수를 사용하였다. 계산된 특징벡터는 BP 신경망의 학습을 통하여 얼굴인식을 위한 데이터로 사용하여 제안된 알고리즘에 의한 인식률향상과 속도 향상을 입증한다.

Linear induction motor(LIM) have static and dynamic end effects due to its finite core length, so that per-phase impedances are asymmetric and the air gap flux distribution is distorted. So, this paper propose the d-q axis equivalent circuit and vector control method considering both static and dynamic end effects of the LIM. This vector control method consists of the slip frequency control, the time-invariant control and decoupling control. As a result, it is shown that the results of equivalent circuit method have a goof agreement with the results of finite element method.

Instantaneous thrust control of linear induction motor(LIM) is needed to control its speed and position more accurately. In the vector control of LIM, it is hard to calculate flux angle exactly because of end effects of LIM. So in this paper direct vector control method is utilized to control speed of LIM. The airgap magnetic flux angle measured by hall sensors is transferred directly into coordinate transformer. As a result, some experimental values of direct vector control using DSP are shown.

Vector control schemes are used in inverter-fed induction motor drives to obtain high performance. Crucial to the success of the vector control scheme is the knowledge of the instantaneous position of the rotor flux. However, the position of the rotor flux change with temperature and magnetic saturation of the motor. This variation cause deterioration of both steady state and dynamic operation of the motor drives. Performance degradation is in the form of input-output torque nonlinearity and saturation of the motor. Analytic expressions are derived to evaluate the effects due to parameter sensitivity. Also, dynamic response is shown by speed command with the variation of stator and rotor resistance.

본 논문에서는 움직임 벡터의 분포특성을 이용한 고속 적응 블럭 정합 알고리즘을 제안하였다. 제안 방법에서는 움직임 벡터에 따른 MAD(0,0)의 분포특성을 분석하여 블럭을 움직임이 없는 블럭, 작은 블럭, 중간정도인 블럭 혹은 큰 블럭으로 분류한 후 각 블럭의 특성에 따라 적응적으로 움직임 벡터를 추정한다. 제안한 방법의 성능을 평가하기 위해서 컴퓨터 시뮬레이션을 수행하였다. 이 결과로부터 제안 방법의 PSNR은 기존의 NTSS 방법과 거의 비슷하면서도 계산량이 30.44% ~ 40.27% 감소되는 효과적인 방법임을 확인할 수 있었다.

We present a fast adaptive block matching algorithm using characteristic of the motion vector distribution. In the presented method, the block is classified into one of four motion categories: stationary block, quasi-stationary block, medium-motion block or high-motion block according to characteristic of the MAD(0,0) distribution for motion vector, each block estiamtes the motion vector adaptively. By the simulation, the PSNR of our algorithm is similar to NTSS method. The computation amount of the presented method decreased 30.44% ~ 40.27% more than NTSS method.

This paper presents dynamic characteristic of permanent magnet synchronous motor using the space vector PWM(pulse-width modulated) which are drove by offset voltage modulation. It is shown by simulation which has the modeling about PWM inverter and PMSM. The validity of dynamic simulation has been confirmed by the phase back-EMF from FEM(Finite Element Methods) under the equal restrict.