• Title/Summary/Keyword: Nonlinear function

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Theoretical Framework For Describing Strain Energy Function on Biomaterial (생체재료를 설명하는 스트레인 에너지 함수에 대한 이론적 고찰)

  • Kang, Taewon
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.1
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    • pp.50-55
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    • 2013
  • In order to understand the biomaterial like the blood vessel of artery, there is a need to quantify the biomechanical behavior of the vessel. However, theoretical framework to describe and quantify the behaviour of blood vessel was not well established so far. For studying the biomechanical behavior of artery, Rubber-liked material which is similar to passive artery is selected since conventional theoretical interpretation is very limited to understand and predict the behavior of biomaterial. Rubber-like material is assumed to be very similar to artery and has properties of isotropy, homogeneity and is undergoing large deformation. Based on this assumption, stress developed on Rubber-like material is described by strain energy function and strain invariants which are required to understand the nonlinear elastic behavior of biomaterial. The descriptor which would be used for understanding the biomechanical behavior of artery is studied in this work.

Nonlinear Function Approximation of Moduled Neural Network Using Genetic Algorithm (유전 알고리즘을 이용한 모듈화된 신경망의 비선형 함수 근사화)

  • 박현철;김성주;김종수;서재용;전홍태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.10-13
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    • 2001
  • Nonlinear Function Approximation of Moduled Neural Network Using Genetic Algorithm Neural Network consists of neuron and synapse. Synapse memorize last pattern and study new pattern. When Neural Network learn new pattern, it tend to forget previously learned pattern. This phenomenon is called to catastrophic inference or catastrophic forgetting. To overcome this phenomenon, Neural Network must be modularized. In this paper, we propose Moduled Neural Network. Modular Neural Network consists of two Neural Network. Each Network individually study different pattern and their outputs is finally summed by net function. Sometimes Neural Network don't find global minimum, but find local minimum. To find global minimum we use Genetic Algorithm.

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A New Method of Finding Real Roots of Nonlinear System Using Extended Fixed Point Iterations (확장된 고정점이론을 이용한 비선형시스템의 근을 구하는 방법)

  • Kim, Sung-Soo;Kim, Ji-Soo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.67 no.2
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    • pp.277-284
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    • 2018
  • In this paper, a new numerical method of finding the roots of a nonlinear system is proposed, which extends the conventional fixed point iterative method by relaxing the constraints on it. The proposed method determines the real valued roots and expands the convergence region by relaxing the constraints on the conventional fixed point iterative method, which transforms the diverging root searching iterations into the converging iterations by employing the metric induced by the geometrical characteristics of a polynomial. A metric is set to measure the distance between a point of a real-valued function and its corresponding image point of its inverse function. The proposed scheme provides the convenience in finding not only the real roots of polynomials but also the roots of the nonlinear systems in the various application areas of science and engineering.

Nonlinear approach to modeling heteroscedasticity in transfer function analysis (시계열 전이함수분석 이분산성의 비선형 모형화)

  • 황선영;김순영;이성덕
    • The Korean Journal of Applied Statistics
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    • v.15 no.2
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    • pp.311-321
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    • 2002
  • Transfer function model(TFM) capturings conditional heteroscedastic pattern is introduced to analyze stochastic regression relationship between the two time series. Nonlinear ARCH concept is incorporated into the TFM via threshold ARCH and beta- ARCH models. Steps for statistical analysis of the proposed model are explained along the lines of the Box & Jenkins(1976, ch. 10). For illustration, dynamic analysis between KOSPI and NASDAQ is conducted from which it is seen that threshold ARCH performs the best.

Induction Motor Position Control Using Integral-Compensating Variable Structure Control Algorithm (적분보상형 가변구조제어기법을 이용한 유도 전동기 위치제어)

  • 강문호
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.6
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    • pp.323-332
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    • 2003
  • This paper proposes a variable structure position controller for an induction motor(IM) which uses a reaching law and an integral compensating nonlinear switching function. With the integral compensating nonlinear switching function, both very low overshoot and high steady state control accuracy can be obtained by compensating the states chattering problem due to the unmodelled dynamics of inverter and feedback sensors. With the reaching law, reaching mode can be established quantitatively during transient state so that dynamic control performance is improved. For experiment a digital servo driver which consists of a DSP and an IPM inverter was developed. With the various experimental results, IM position control performance was verified.

Derivation of a Group of Lyapunov Functions reflecting Damping Effects and its Application (댐핑 영향을 반영하는 Lyapunov 함수 그룹의 유도 및 응용)

  • Moon, Y.H.;Choi, B.K.;Roh, T.H.;Lee, T.S.;Lee, Y.S.
    • Proceedings of the KIEE Conference
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    • 1995.11a
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    • pp.195-198
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    • 1995
  • Most of the theorems of nonlinear stability is based on the Lyapunov stability theory. The Lyapunov function method is the most well-known and provides precise and rigorous theoretical backgrounds. However, tile conventional approach to direct stability analysis has been performed without taking account of damping effects. For accurate stability analysis of nonlinear systems, it is required to consider the damping effects. This paper presents a new method to derive a group of Lyapunov functions to reflect the damping effects by considering the integral relationships of the system governing equations. This method tan be utilized as a powerful tool to determine the region of attraction.

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SOLVING NONLINEAR ASSET LIABILITY MANAGEMENT PROBLEMS WITH A PRIMAL-DUAL INTERIOR POINT NONMONOTONE TRUST REGION METHOD

  • Gu, Nengzhu;Zhao, Yan
    • Journal of applied mathematics & informatics
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    • v.27 no.5_6
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    • pp.981-1000
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    • 2009
  • This paper considers asset liability management problems when their deterministic equivalent formulations are general nonlinear optimization problems. The presented approach uses a nonmonotone trust region strategy for solving a sequence of unconstrained subproblems parameterized by a scalar parameter. The objective function of each unconstrained subproblem is an augmented penalty-barrier function that involves both primal and dual variables. Each subproblem is solved approximately. The algorithm does not restrict a monotonic decrease of the objective function value at each iteration. If a trial step is not accepted, the algorithm performs a non monotone line search to find a new acceptable point instead of resolving the subproblem. We prove that the algorithm globally converges to a point satisfying the second-order necessary optimality conditions.

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Design of Adaptive Discrete Time Sliding-Mode Tracking Controller for a Hydraulic Proportional Control System Considering Nonlinear Friction (비선형 마찰을 고려한 유압비례제어 시스템의 적응 이산시간 슬라이딩모드 추적 제어기 설계)

  • Park, H.B.
    • Journal of Power System Engineering
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    • v.9 no.4
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    • pp.175-180
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    • 2005
  • Incorrections between model and plant are parameter, system order uncertainties and modeling error due to disturbance like friction. Therefore to achieve a good tracking performance, adaptive discrete time sliding mode tracking controller is used under time-varying desired position. Based on the diophantine equation, a new discrete time sliding function is defined and utilized for the control law. Robustness is increased by using both a recursive least-square method and a sliding function-based nonlinear feedback. The effectiveness of the proposed control algorithm is proved by the results of simulation and experiment.

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An Application of the Monte Carlo Method to the Economical Circuit Design in Consideration of the Drift Reliability (표류신뢰도를 고려한 경제적 회로 설계에 대한 몬테칼로법의 적용)

  • Kyun-Hyon Tchah
    • 전기의세계
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    • v.24 no.5
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    • pp.72-80
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    • 1975
  • In this paper an application of the Monte Carlo method to optimum circuit design is discussed. T. Tsuda and T. Kiyono's algorithm based on the Monte Carlo method for solving multiple simul-taneous nonlinear equations is generalized to apply it to finding solutions of the constrained nonlinear optimization problem. The generalized algorithm derived here is directly applied to economical circuit design. In the cirsuit design, the object function is a cost function which is related to the cost of each circuit component. The constraint is the variance of the total system expressed by the variances of each circuit component. The design is to be determined so that the circuit has specified drift reliability with minimum cost. A practical example of economical circuit design and a general nonlinear function minimization is presented with food results.

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Seismic performance of skewed highway bridges using analytical fragility function methodology

  • Bayat, M.;Daneshjoo, F.
    • Computers and Concrete
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    • v.16 no.5
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    • pp.723-740
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    • 2015
  • In this study, the seismic performance of skewed highway bridges has been assessed by using fragility function methodology. Incremental Dynamic Analysis (IDA) has been used to prepare complete information about the different damage states of a 30 degree skewed highway bridge. A three dimensional model of a skewed highway bridge is presented and incremental dynamic analysis has been applied. The details of the full nonlinear procedures have also been presented. Different spectral intensity measures are studied and the effects of the period on the fragility curves are shown in different figures. The efficiency, practicality and proficiency of these different spectral intensity measures are compared. A suite of 20 earthquake ground motions are considered for nonlinear time history analysis. It has been shown that, considering different intensity measures (IM) leads us to overestimate or low estimate the damage probability which has been discussed completely.