• Proceedings of the KIEE Conference
• /
• 2004.07d
• /
• pp.2528-2530
• /
• 2004

Neural network minimization problems are often conditioned and in this contribution way to handle this will be discussed. It is shown that a better conditioned minimization problem can be obtained if the problem is separated with respect to the linear parameters. This will increase the convergence speed of the minimization. One of the most powerful uses of neural networks is in function approximation(curve fitting)[1]. A main characteristic of this solution is that function (f) to be approximated is given not explicitly but implicitly through a set of input-output pairs, named as training set, that can be easily obtained from calibration data of the measurement system. In this context, the usage of Neural Network(NN) techniques for modeling the systems behavior can provide lower interpolation errors when compared with classical methods like polynomial interpolation. This paper solve of single-variable minimization using neural network.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.9
• /
• pp.71-81
• /
• 2001

This paper analyzes the effectiveness of minimizing vibration and sound transmission on/through a thin rectangular plate by both feedback control and hybrid control which combines adaptive feedforward control with a feedback loop. An experimental system identification technique using the matrix-fractional curve-fitting of the frequency response data is introduced for complex shaped structures. This identification technique reduces the model order o the MIMO(Multi-Input Multi-Output) system which simplifies the practical implementation. The adaptive feedforward control uses a Multiple filtered-x LMS(Least Mean Square) algorithm and the feedback control uses a multivariable digital LQG(Linear Quadratic Gaussian) algorithm. Experimental results show that an effective reduction of sound transmission is achieved by the hybrid control scheme when both vibration and noise measurement signals are incorporated in the controller.

• Geomechanics and Engineering
• /
• v.23 no.5
• /
• pp.431-439
• /
• 2020

Soil-water retention curve (SWRC) contains key information for the application of unsaturated soil mechanics principles to engineering practice. The SWRC variables are commonly used to describe the hydro-mechanics of soils. Generally, these parameters are determined using the graphical method which can be time consuming. The SWRC is highly dependent on the pore size distribution (PSD). Theoretically, the PSD obtained by mercury intrusion porosimetry test can be used to determine some SWRC variables. Moreover, the relationship between SWRC and shrinkage curve has been investigated. A new method to determine total SWRC variables directly without curve-fitting procedure is proposed. Substituting the variables into linear SWRC equations construct SWRC. A good agreement was obtained between predicted and measured SWRCs, indicating the validity of the proposed method for unimodal SWRC.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.238-243
• /
• 1986

Distillation columns are widely used in almost every chemical plant. The use of multivariable control for such units is attractive because of the strong interactions exhibited between outputs and inputs and the desire to control simultaneously both top and bottom products. In this research design of a robust multivariable controller for distillation column was considered; output feedback controller with proportional and integral modes was designed using pole assignment. The transfer function matrix was obtained by fitting the step response realtions between single input double output pairs of variables. This matrix was then converted to linear time invariant state space model by multivariable realization technique. With the proposed multivariable proportional and integral controller applied to the process, the result of the digital computer simulation showed a good performance of asymtotic tracking. The limited experimental performance of this multivariable control was compared with the result from simulation. It was found that the proposed controller performed satisfactorily for the distillation column which separated binary mixture of methanol and water.

• Communications for Statistical Applications and Methods
• /
• v.16 no.4
• /
• pp.697-705
• /
• 2009

The Pearson chi-squared statistic or the deviance statistic is widely used in assessing the goodness-of-fit of the generalized linear models. But these statistics are not proper in the situation of continuous explanatory variables which results in the sparseness of cell frequencies. We propose a goodness-of-fit test statistic for the cumulative logit models with ordinal responses. We consider the grouping of a dataset based on the ordinal scores obtained by fitting the assumed model. We propose the Pearson chi-squared type test statistic, which is obtained from the cross-classified table formed by the subgroups of ordinal scores and the response categories. Because the limiting distribution of the chi-squared type statistic is intractable we suggest the parametric bootstrap testing procedure to approximate the distribution of the proposed test statistic.

• Journal of the Korean Ceramic Society
• /
• v.48 no.6
• /
• pp.577-583
• /
• 2011

Stabilized biocompatible superparamagnetic iron oxide nanoparticles (SPIONs) were prepared by controlled coprecipitation method for hyperthermia application. ESR measurements determined that all of the interactions in the individual SPIONs (1 nm and 11 nm) were antiferromagnetic in nature because the ions contributed to the magnetization with a range of magnetic moments. In-situ monitoring of the temperature increment was performed, showing that the microwave absorption rate of the SPIONs was dispersed in an appropriate host media (polar or non-polar solvents) during microwave irradiation. Microwave absorption energy rates and heat loss of SPIONs in solvent were calculated by non-linear data fitting with an energy balance equation. The microwave absorption rates of SPIONs dispersed in solvent linearly increases when the concentration of SPIONs increases, implying that the microwave absorption rate can be tunable by changing the concentration of SPIONs.

• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.6
• /
• pp.345-352
• /
• 2014

Edge detection considers the important technical details of digital image processing. Many edge detection operators already perform edge detection in digital color imaging. In this study, the edge of many real color images that represent the type of digital image was detected using a new operator in the least square approximation method, which is a type of numerical method. The Linear Fitting algorithm is computationally more expensive compared to the Canny, LoG, Sobel, Prewitt, HIS, Fuzzy, Parametric, Synthetic and Vector methods, and Robert' operators. The results showed that the new method can detect an edge in a digital color image with high efficiency compared to standard methods used for edge detection. In addition, the suggested operator is very useful for detecting the edge in a digital color image.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.20 no.11
• /
• pp.1171-1177
• /
• 2009

A missile warning radar is an essential sensor for active protection system to detect antitank missile in all weather environments. This paper introduces missile warning radar for main battle tank and presents the results of the design and implementation of the radar signal processor using high speed multi-DSP. The key algorithms include adaptive CF AR, weighted linear fitting algorithm, S/W tracking capability, and threat decision and present test result.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.3
• /
• pp.227-230
• /
• 2002

A new iris segmentation and recognition method is described. Combining a statistical classification and elastic boundary fitting, the iris is first segmented robustly and accurately. Once the iris is segmented, one-dimensional signals are computed in the iris and decomposed into multiple frequency bands. Each decomposed signal is approximated by a piecewise linear curve connecting a small set of node points. The node points represent features of each signal. The similarity measture between two iris images is the normalized cross-correlation coefficients between simplified signals.

• Communications for Statistical Applications and Methods
• /
• v.13 no.1
• /
• pp.177-190
• /
• 2006

The aim of this study is to propose a Bayesian model for fitting mortality rate of colon cancer. For the analysis of mortality rate of a disease, factors such as age classes of population and spatial characteristics of the location are very important. The model proposed in this study allows the age class to be a random effect in addition to its conventional role as the covariate of a linear regression, while the spatial factor being a random effect. The model is fitted using Metropolis-Hastings algorithm. Posterior expected predictive deviances, standardized residuals, and residual plots are used for comparison of models. It is found that the proposed model has smaller residuals and better predictive accuracy. Lastly, we described patterns in disease maps for colon cancer.