• Title/Summary/Keyword: parameter function

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Kernel Analysis of Weighted Linear Interpolation Based on Even-Odd Decomposition (짝수 홀수 분해 기반의 가중 선형 보간법을 위한 커널 분석)

  • Oh, Eun-ju;Yoo, Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.11
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    • pp.1455-1461
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    • 2018
  • This paper presents a kernel analysis of weighted linear interpolation based on even-odd decomposition (EOD). The EOD method has advantages in that it provides low-complexity and improved image quality than the CCI method. However, since the kernel of EOD has not studied before and its analysis has not been addressed yet, this paper proposes the kernel function and its analysis. The kernel function is divided into odd and even terms. And then, the kernel is accomplished by summing the two terms. The proposed kernel is adjustable by a parameter. The parameter influences efficiency in the EOD based WLI process. Also, the kernel shapes are proposed by adjusting the parameter. In addition, the discussion with respect to the parameter is given to understand the parameter. A preliminary experiment on the kernel shape is presented to understand the adjustable parameter and corresponding kernel.

Design of Adaptive Neural Networks Based Path Following Controller Under Vehicle Parameter Variations (차량 파라미터 변화에 강건한 적응형 신경회로망 기반 경로추종제어기)

  • Shin, Dong Ho
    • Journal of Drive and Control
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    • v.17 no.1
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    • pp.13-20
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    • 2020
  • Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

Performance Comparison of Four-Parameter Correlation Equations of the Enthalpy of Vaporization

  • Lee, Kyoung-Youl;Park, Kyoung-Kuhn
    • International Journal of Air-Conditioning and Refrigeration
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    • v.14 no.3
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    • pp.118-123
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    • 2006
  • A few commonly used correlation equations of the enthalpy of vaporization essential to the analysis of refrigeration cycles are reviewed. A new four-parameter correlation equation is proposed assuming that the enthalpy of vaporization could be represented with a linear form of the temperature and an additional function which slowly decreases as the temperature increases. It is not a common practice to measure the enthalpy of vaporization by experiment; therefore, performance of the new correlation is examined using numeric data from the ASHRAE tables for 22 pure substance refrigerants. The new correlation equation and other existing ones are fitted to the data optimizing the root mean squared deviation. All data points are weighted equally and NBP (normal boiling point) is used as a fixed point since the NBP is important for refrigeration application. The new four-parameter equation yields an average absolute deviation of 0.05% for 22 refrigerants which is smaller than those of other four-parameter equations, such as Guermouche-Vergnaud (0.08%), Aerebrot (0.13%), Radoz-Lyderson (0.08%), and Somayajulu four-parameter equation (0.08%).

Determination of Minimum Eigenvalue in a Continuous-time Weighted Least Squares Estimator (연속시간 하중최소자승 식별기의 최소고우치 결정)

  • Kim, Sung-Duck
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.9
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    • pp.1021-1030
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    • 1992
  • When using a least squares estimator with exponential forgetting factor to identify continuous-time deterministic system, the problem of determining minimum eigenvalue is described in this paper. It is well known fact that the convergence rate of parameter estimates relies on various factors consisting of the estimator and especially, theirproperties can be directly affected by all eigenvalues in the parameter error differential equation. Fortunately, there exists only one adjusting eigenvalue in the given estimator and then, the parameter convergence rates depend on this minimum eigenvalue. In this note, a new result to determine the minimum eigenvalue is proposed. Under the assumption that the input has as many spectral lines as the number of parameter estimates, it can be proven that the minimum eigenvalue converges to a constant value, which is a function of the forgetting factor and the parameter estimates number.

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Separation Effect Analysis for Rainfall Data (강우자료의 분리효과)

  • 김양수;허준행
    • Water for future
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    • v.26 no.4
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    • pp.73-83
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    • 1993
  • This study focuses on the separation effect analysis of rainfall data for 2-parameter log-normal, 3-parameter log-normal, type-extreme value, 2-parameter gamma, 3-parameter gamma, log-Pearson type-III, and general extreme value distribution functions. Difference in the relationship between the mean and standard deviation of skewness for historical data and relations derived from 7 distribution functions are analyzed suing the Monte Carlo experiment. The results show that rainfall data has the separation effect for 6 distribution functions except 3-parameter gamma distribution function.

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A Study on The Coarse-to-fine Extraction Method of function Patterns by using The Dynamic Quantization of Parameter Space (매개변수공간의 동적 분할 방법에 의한 함수패턴의 단계적 분석 추출에 관한 연구)

  • 김민환;황희영
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.8
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    • pp.594-602
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    • 1987
  • This paper proposes a new method of reducing the processing time and the size of consummimg memories in Hough transform. In this method, only the functional patterns are considered. The candidate points which are accumulated into the parameter space are computed in a many-to-one fashion and the parameter space is quantized dynamically to maintain a fine precision where it is needed. And a coarse-to-fine extraction method is used to reduce the processing time. The many-to-one fashional computation results in a relatively high-densed accumulation of candidate points around the parameter points corresponding to the image patterns in the image space. So, the dynamic quantization procedure can be simplified and the local maxima can be determined easily. And more effective reduction can be obtained as the dimension of parameter space is increased.

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Relation between molecular structure and order parameter of liquid crystals and dyes in GH-LCD (GH형 LCD에 있어서 액정 및 2색성 색소의 분자형상과 배향질서도와의 관계)

  • 박우상
    • Electrical & Electronic Materials
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    • v.10 no.10
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    • pp.989-994
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    • 1997
  • In a Guest-Host cell the orientational ordering of dyes doped into liquid crystals has been investigated. To evaluate the influence of the host liquid crystals on the ordering of the dyes we have measured precisely the ordering parameters of the liquid crystals by using the dichroic ratio of the absorbances for infrared light polarized parallel and perpendicular to the diector. Our experimental results show that the ordering of the dyes can be expressed as a function of not only the molecular structure of the dyes but also the order parameter of the liquid crystals. These functions are dependent on the kinds of the liquid crystals and the dyes. Particularly the combination such as anthraquinone dyes doped into cyanobiphenyl liquid crystals show a very high ordering parameter. This is considered due to a strong intermolecular interaction between the dipoles of both liquid crystals and dyes.

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A convenient approach for penalty parameter selection in robust lasso regression

  • Kim, Jongyoung;Lee, Seokho
    • Communications for Statistical Applications and Methods
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    • v.24 no.6
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    • pp.651-662
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    • 2017
  • We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

Parameter-dependent Robust Stability of Uncertain Singular Systems with Time-varying Delays (시변 시간지연을 가지는 불확실 특이시스템의 변수 종속 강인 안정성)

  • Kim, Jong-Hae
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.4
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    • pp.1-6
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    • 2010
  • In this paper, we present a new delay-dependent and parameter-dependent robust stability condition for uncertain singular systems with polytopic parameter uncertainties and time-varying delay. The robust stability criterions based on parameter-dependent Lyapunov function are expressed as LMI (linear matrix inequality). Moreover, the proposed robust stability condition is a general algorithm for both singular systems and non-singular systems. Finally, numerical examples are presented to illustrate the feasibility and less conservativeness of the proposed method.

Comparison of different estimators of P(Y

  • Hassan, Marwa KH.
    • International Journal of Reliability and Applications
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    • v.18 no.2
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    • pp.83-98
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    • 2017
  • Stress-strength reliability problems arise frequently in applied statistics and related fields. In the context of reliability, the stress-strength model describes the life of a component, which has a random strength X and is subjected to random stress Y. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X > Y. The problem of estimation the reliability parameter in a stress-strength model R = P[Y < X], when X and Y are two independent two-parameter Lindley random variables is considered in this paper. The maximum likelihood estimator (MLE) and Bayes estimator of R are obtained. Also, different confidence intervals of R are obtained. Simulation study is performed to compare the different proposed estimation methods. Example in real data is used as practical application of the proposed procedure.

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