• International Journal of Precision Engineering and Manufacturing
• /
• 제4권2호
• /
• pp.64-70
• /
• 2003

A new method using a transfer function is introduced in the present paper for analyzing the motion errors of hydrostatic bearing tables. The relationship between film reaction force in a single-side hydrostatic pad and the form error of guide rail is derived at various spatial frequencies by finite element analysis, and it is expressed as a transfer function. This transfer function clarifies so called 'the averaging effect of an oil film' quantitively. It is found that the amplitude of film force is reduced as the spatial frequency increases or the relative width of the pocket is reduced. The motion errors of a multi pad type table are estimated using a transfer function, the form errors of a guide rail and the geometric relationship between the pads. The method is named as the Transfer Function Method (TFM). The motion errors calculated by the TFM show good agreement with the motion errors calculated by the Multi Pad Method considering the entire table as an analysis object. From the results, it is confirmed that the proposed TFM is very effective to analyze the motion errors of hydrostatic tables.

• 한국컴퓨터정보학회논문지
• /
• 제16권12호
• /
• pp.11-21
• /
• 2011

임베디드 센서는 낮은 전력량과 신호의 세기로 장애물이나 거리와 같은 공간 환경에 많은 영향을 받으며, 이러한 원인들로 인해 임베디드 센서에서는 노이즈 데이터가 빈번히 발생한다. 임베디드 센서에서 획득하는 정보는 시계열 데이터로 존재하기 때문에 지속적으로 발생하는 시계열 정보에 대한 오류 검출을 실시간적으로 수행하기는 어렵다. 본 논문에서는 임베디드 장치의 물리적 특성을 고려하여 실시간적으로 발생하는 임베디드 센서의 오류 신호를 검출하는 시계열 예측 기반 오류 검출 기법을 제안한다. 본 논문에서 제안한 시계열 예측 기반 오류 검출 기법은 안정 구간 함수를이용하여 현재 발생하는 임베디드장치 신호의 오류를 판단한다. 안정 구간 함수는 임베디드장치 신호를 관측하여 오류 검출을 수행할 때 최근의 신호들에 오류 가중화를 적용함으로써 효과적으로 오류 신호를 탐지할 수 있다. 본 논문에서 제안한 기법을 Intel Lab 신호를 이용하여 실험하였으며, 실험에서 본 논문에서 제안한 기법은 중심이동평균 기법에 비해 26.25%의 정확도 향상을 나타내었다.

• 응용통계연구
• /
• 제27권3호
• /
• pp.419-430
• /
• 2014

전력수급의 정확한 예측은 국민들의 일상적 생활 유지, 산업활동, 그리고 국가경영을 위하여 매우 중요하다. 본 연구에서는 시계열모형화에 의해 전력판매량을 예측한다. 실제 자료분석을 통하여 입력시계열로서 냉난방도일과 개입변수로 펄스함수를 사용한 전이함수모형이 다른 시계열모형에 비해서 제곱근평균제곱오차 및 평균절대오차의 의미에서 더 우수하였다.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.300-302
• /
• 2006

Middleware offers function that user application program can transmit data independently of network device. Connection management about network connection of module is important for normal service of module base personal robot. Unpredictable network disconnection is influenced to whole robot performance in module base personal robot. For this, Middleware must be offer two important function. The first is function of error detection and reporting about abnormal network disconnection. Therefore, middleware need method for network error detection and module management to consider special quality that each network device has. The second is the function recovering that makes the regular service possible. When the module closed from connection reconnects, as this service reports connection state of the corresponding module, the personal robot resumes the existing service. In this paper proposed method of network connection management for to support fault tolerant about network error of network module based personal robot.

• Journal of applied mathematics & informatics
• /
• 제7권1호
• /
• pp.61-82
• /
• 2000

In this paper two so-called regularized Green's functions are introduced to derive the optimal maximum norm error estimates for the unknown function and the adjoint vector-valued function for mixed finite element methods of Laplacian operator. One contribution of the paper is a demonstration of how the boundedness of $L^1$-norm estimate for the second Green's function ${\lambda}_2$ and the optimal maximum norm error estimate for the adjoint vector-valued function are proved. These results are seemed to be to be new in the literature of the mixed finite element methods.

• Communications for Statistical Applications and Methods
• /
• 제3권1호
• /
• pp.243-255
• /
• 1996

The number of neutron signals from a neutral particle beam(NPB) at the detector, without any errors, obeys Poisson distribution, Under two assumptions that NPB scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of signals becomes a Poisson-power function distribution. In this paper, we show that the error rate in simple hypothesis testing for the limiting Poisson-power function distribution is not zero. That is, the limit of ${\alpha}+{\beta}$ is zero when Poisson parameter$\kappa\rightarro\infty$, but this limit is not zero (i.e., $\rho\ell$>0)for the Poisson-power function distribution. We also give optimal decision algorithms for a specified error rate.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2015년도 추계학술대회
• /
• pp.1045-1046
• /
• 2015

When using the Support Vector Machine in the online signature verification, SVM kernel function should be chosen to use non-linear SVM and the constant parameters in the kernel functions should be adjusted to appropriate values to reduce the error rate of signature verification. Non-linear SVM which is built on a strong mathematical basis shows better performance of classification with the higher discrimination power. However, choosing the kernel function and adjusting constant parameter values depend on the heuristics of the problem domain. In the signature verification, this paper deals with the problems of selecting the correct kernel function and constant parameters' values, and shows the kernel function and coefficient parameter's values with the minimum error rate. As a result of this research, we expect the average error rate to be less than 1%.

• 전자공학회논문지B
• /
• 제29B권1호
• /
• pp.94-101
• /
• 1992

The multilayer perceptron, trained by the error back-propagation learning rule, has been known as a mapping network which can represent arbitrary functions. However depending on the complexity of a function and the initial weights of the multilayer perceptron, the error back-propagation learning may fall into a local minimum or a flat area which may require a long learning time or lead to unsuccessful learning. To solve such difficulties in training the multilayer perceptron by standard error back-propagation learning rule, the paper proposes a learning method which progressively enlarges the learning domain from a small area to the entire region. The proposed method is devised from the investigation on the roles of hidden nodes and connection weights in the multilayer perceptron which approximates a function of one variable. The validity of the proposed method was illustrated through simulations for a function of one variable and a function of two variable with many extremal points.

• 한국자동차공학회논문집
• /
• 제10권5호
• /
• pp.29-34
• /
• 2002

This study presents the process of the continuous-time system identification for unknown nonlinear systems. The Radial Basis Function(RBF) error filtering identification model is introduced at first. This identification scheme includes RBF network to approximate unknown function of nonlinear system which is structured by affine form. The neural network is trained by the adaptive law based on Lyapunov synthesis method. The identification scheme is applied to engine and the performance of RBF error filtering Identification model is verified by the simulation with a three-state engine model. The simulation results have revealed that the values of the estimated function show favorable agreement with the real values of the engine model. The introduced identification scheme can be effectively applied to model-based nonlinear control.

• 대한수학회지
• /
• 제48권3호
• /
• pp.655-667
• /
• 2011

A class of functions involving divided differences of the psi and tri-gamma functions and originating from Kershaw's double inequality are proved to be completely monotonic. As applications of these results, the monotonicity and convexity of a function involving the ratio of two gamma functions and originating from the establishment of the best upper and lower bounds in Kershaw's double inequality are derived, two sharp double inequalities involving ratios of double factorials are recovered, the probability integral or error function is estimated, a double inequality for ratio of the volumes of the unit balls in $\mathbb{R}^{n-1}$ and $\mathbb{R}^n$ respectively is deduced, and a symmetrical upper and lower bounds for the gamma function in terms of the psi function is generalized.