• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.268-272
• /
• 1996

Error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with some experimental results.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.4
• /
• pp.57-63
• /
• 2010

The damping parameter of Levenberg-Marquardt algorithm switches between error backpropagation and Gauss-Newton learning and affects learning speed. Fixing the damping parameter induces some oscillation of error and decreases learning speed. Therefore, we propose the way of a variable damping parameter with referring to the alternation of error. The proposed method makes the damping parameter increase if error rate is large and makes it decrease if error rate is small. This method so plays the role of momentum that it can improve learning speed. We tested both iris recognition and wine recognition for this paper. We found out that this method improved learning speed in 67% cases on iris recognition and in 78% cases on wine recognition. It was also showed that the oscillation of error by the proposed way was less than those of other algorithms.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.05b
• /
• pp.109-114
• /
• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The camera calibration is a necessary procedure for stereo vision-based depth computation. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. No effective methods for such alignment have been presented before. Some amount of depth error caused from such non-parallel installation of cameras is inevitable. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2005.07a
• /
• pp.605-606
• /
• 2005

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.12
• /
• pp.1-11
• /
• 1993

This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.664-667
• /
• 1996

This paper presents the error parameter estimation technique for IMU(Inertial Measurement Unit) which is core sensor of INS(Inertial Navigation System) and verifies it via laboratory test. Firstly the error characteristic of gyroscope and accelerometer which is contained in IMU is examined and the error modelling is executed. The error of IMU can be divided into deterministic and random part, and the deterministic error can be divided into static and dynamic part. This paper consider the random part as constant. Secondly the error parameter estimation technique and following procedure for laboratory test is explained. Thirdly according to the test procedure the IMU test for static error is executed using 2-axis rate table and estimation result is presented with discussion about its validity.

• The Journal of the Acoustical Society of Korea
• /
• v.15 no.3E
• /
• pp.78-85
• /
• 1996

The set of admissible time-variations in the input signal can be separated into two categories : slow parameter changes and large parameter changes which occur infrequently. A common approach used in the tracking of slowly time-varying parameters is the exponential recursive least-squares(RLS) algorithm. There have been a variety of research works on the error analysis of the exponential RLS algorithm for the slowly time-varying parameters. In this paper, the focus has been given to the error analysis of exponential RLS algorithms for the input data with abrupt property changes. The voiced speech signal is chosen as the principal application. In order to analyze the error performance of the exponential RLS algorithm, deterministic properties of the exponential RLS algorithms is first analyzed for the case of abrupt parameter changes, the impulsive input(or error variance) synchronous to the abrupt change of parameter vectors actually enhances the convergence of the exponential RLS algorithm. The analysis has also been verified through simulations on the synthetic speech signal.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.20 no.11
• /
• pp.3549-3559
• /
• 1996

In this study, the effect of parameter and modal filter errors on the vibration control characteristics of flexible structures is analyzed for IMSC ( Independent Modal Space Control). If the control force is designed on the basis of the mathematical model with the parameter and modal filter errors, the closed-loop performance of the vibration control system will be degraded depending on the magnitude of the errors. An asymptotic stability condition of the system with parameter and modal filter errors has more significant effect on the stability condition of the system with parameter and modal filter errors has been drived using Lyapunov approach. It has been found that modal filter error has more significant effect on the stability of closed-loop system than parameter error does. The extent of the response deviation of the closed-loop system is also derived and evaluated using operator thchniques.

• Steel and Composite Structures
• /
• v.20 no.5
• /
• pp.1119-1131
• /
• 2016

As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen's nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.25 no.3
• /
• pp.227-234
• /
• 2020

This paper presents the methods for the modeling and parameter optimization of the electric vehicle battery. The state variables of the battery are defined, and the test methods for battery parameters are presented. The state-space equation, which consists of four state variables, and the output equation, which is a combination of to-be-determined parameters, are shown. The parameter optimization method is the key point of this study. The least square of the modeling error can be used as an initial value of the multivariable function. It is equivalent to find the minimum value of the error function to obtain optimal parameters from multivariable function. The SIMULINK model is presented, and the 10-hour full operational range test results are shown to verify the performance of the model. The modeling error for 25 degrees is approximately 1% for full operational ranges. The comments to enhance modeling accuracy are shown in the conclusion.