• 제목/요약/키워드: Global linear convergence

검색결과 64건 처리시간 0.216초

ANALYSIS OF A SMOOTHING METHOD FOR SYMMETRIC CONIC LINEAR PROGRAMMING

  • Liu Yong-Jin;Zhang Li-Wei;Wang Yin-He
    • Journal of applied mathematics & informatics
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    • 제22권1_2호
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    • pp.133-148
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    • 2006
  • This paper proposes a smoothing method for symmetric conic linear programming (SCLP). We first characterize the central path conditions for SCLP problems with the help of Chen-Harker-Kanzow-Smale smoothing function. A smoothing-type algorithm is constructed based on this characterization and the global convergence and locally quadratic convergence for the proposed algorithm are demonstrated.

연산회로 신경망 (Computational Neural Networks)

  • 강민제
    • 융합신호처리학회논문지
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    • 제3권1호
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    • pp.80-86
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    • 2002
  • 아날로그 합산과 선형방정식을 풀 수 있는 신경망구조가 제안되었다. 계산에너지함수에 근거하여 가중치를 구하는 Hopfield 신경망모델을 사용하였다. 아날로그 합산과 선형방정식은 각각 Hopfiled의 A/D컨버터와 선형프로그래밍회로망을 이용하여 설계되었다. 시뮬레이션은 Pspice 프로그램을 이용하였으며, 그 결과들은 대부분 전체극소점으로 수렴함을 보였다.

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AN ADAPTIVE APPROACH OF CONIC TRUST-REGION METHOD FOR UNCONSTRAINED OPTIMIZATION PROBLEMS

  • FU JINHUA;SUN WENYU;SAMPAIO RAIMUNDO J. B. DE
    • Journal of applied mathematics & informatics
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    • 제19권1_2호
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    • pp.165-177
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    • 2005
  • In this paper, an adaptive trust region method based on the conic model for unconstrained optimization problems is proposed and analyzed. We establish the global and super linear convergence results of the method. Numerical tests are reported that confirm the efficiency of the new method.

다중 UAV에 의해 획득된 거리 차 측정치를 이용한 순환 선형 강인 이동 표적추적 필터 (Recursive Linear Robust Moving Target Tracking Filter Using Range Difference Information Measured by Multiple UAVs)

  • 이혜경;나원상
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.1738-1739
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    • 2011
  • In this paper, the range difference based the moving target tracking problem using multiple UAVs is solved within the new framework of linear robust state estimation. To do this, the relative kinematics is modeled as an uncertain linear system containing stochastic parametric uncertainties in its measurement matrix. Applying the non-conservative robust Kalman filter for the uncertain system, a quasi-optimal linear target tracking filter is designed. For its recursive linear filter structure, the proposed method can ensure the fast convergence and reliable target tracking performance. Moreover, it is suitable for real-time applications using multiple UAVs.

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Position Sensorless Control of BLDC Motors Based on Global Fast Terminal Sliding Mode Observer

  • Wang, Xiaoyuan;Fu, Tao;Wang, Xiaoguang
    • Journal of Power Electronics
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    • 제15권6호
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    • pp.1559-1566
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    • 2015
  • The brushless DC motor (BLDCM) has many advantages. As a result, it is widely used in electric vehicle (EV) drive systems. To improve the reliability of the motor control system, a position sensorless control strategy based on a sliding mode observer (SMO) is proposed. The global fast terminal sliding mode observer (GFTSMO) is proposed to enhance the control performance of the SMO control system. The advantages of the linear sliding mode and the nonsingular terminal sliding mode (NTSM) are combined in the control strategy. The convergence speed of the system state is enhanced. The motor commutation point is obtained with the observation of the back EMF, and the instantaneous torque value of the motor is calculated. Therefore, the position sensorless control of the BLDCM is realized. Experimental results show that the proposed control strategy can improve the convergence speed, dynamic characteristics and robustness of the system.

Estimation of Soil Organic Carbon Stock in South Korea

  • Thi, Tuyet-May Do;Le, Xuan-Hien;Van, Linh Nguyen;Yeon, Minho;Lee, Giha
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.159-159
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    • 2022
  • Soil represents a substantial component within the global carbon cycle and small changes in the SOC stock may result in large changes of atmospheric CO2 particularly over tens to hundreds of years. In this study, we aim to (i) evaluate the SOC stock in the topsoil 0 - 15 cm from soil physical and chemical characteristics and (ii) find the correlation of SOC and soil organic matter (SOM) for national-scale in South Korea. First of all, based on the characteristics of the soil to calculate the soil hydraulic properties, SOC stock is the SOC mass per unit area for a given depth. It depends on bulk density (BD-g/cm3), SOC content (%), the depth of topsoil (cm), and gravel content (%). Due to insufficient data on BD observation, we establish a correlation between BD and SOC content, sand content, clay content parameter. Next, we present linear and non-linear regression models of BD and the interrelationship between SOC and SOM using a linear regression model and determine the conversion factor for them, comparing with Van Bemmelen 1890's factor value for the country scale. The results obtained, helps managers come up with suitable solutions to conserve land resources.

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세계 경제 지표를 활용한 머신러닝 기반 국제 경유 가격 예측 모델 개발 (International Diesel Price Prediction Model based on Machine Learning with Global Economic Indicators)

  • 최아린;박민서
    • 문화기술의 융합
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    • 제9권6호
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    • pp.251-256
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    • 2023
  • 국제 경유 가격은 산업, 교통 및 에너지 생산과 같은 여러 분야에서 중요한 역할을 수행하며, 세계 경제와 국제 무역에도 큰 영향을 미친다. 특히, 국제 경유 가격의 상승은 소비자에게 부담을 주고 인플레이션의 원인이 될 수있다. 그러나 기존 연구들은 주로 휘발유에 초점을 맞추어 진행되었다. 따라서 본 연구는 국제 경유 가격 예측 모델을 제안하고자 한다. 이를 위해 다양한 세계 경제 지표들을 활용하여 머신러닝 방법론 중 하나인 선형 회귀 모델로 학습한다. 해당 모델은 세계 경제 지표들과 국제 경유 가격 간의 관계를 명확하게 파악함과 동시에 높은 정확도로 예측한다. 이는 시장 변화를 비롯한 전반적인 경제 흐름 파악에 도움이 될 것으로 기대된다.

ON THE GLOBAL CONVERGENCE OF A MODIFIED SEQUENTIAL QUADRATIC PROGRAMMING ALGORITHM FOR NONLINEAR PROGRAMMING PROBLEMS WITH INEQUALITY CONSTRAINTS

  • Liu, Bingzhuang
    • Journal of applied mathematics & informatics
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    • 제29권5_6호
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    • pp.1395-1407
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    • 2011
  • When a Sequential Quadratic Programming (SQP) method is used to solve the nonlinear programming problems, one of the main difficulties is that the Quadratic Programming (QP) subproblem may be incompatible. In this paper, an SQP algorithm is given by modifying the traditional QP subproblem and applying a class of $l_{\infty}$ penalty function whose penalty parameters can be adjusted automatically. The new QP subproblem is compatible. Under the extended Mangasarian-Fromovitz constraint qualification condition and the boundedness of the iterates, the algorithm is showed to be globally convergent to a KKT point of the non-linear programming problem.

A SMOOTHING NEWTON METHOD FOR NCP BASED ON A NEW CLASS OF SMOOTHING FUNCTIONS

  • Zhu, Jianguang;Hao, Binbin
    • Journal of applied mathematics & informatics
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    • 제32권1_2호
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    • pp.211-225
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    • 2014
  • A new class of smoothing functions is introduced in this paper, which includes some important smoothing complementarity functions as its special cases. Based on this new smoothing function, we proposed a smoothing Newton method. Our algorithm needs only to solve one linear system of equations. Without requiring the nonemptyness and boundedness of the solution set, the proposed algorithm is proved to be globally convergent. Numerical results indicate that the smoothing Newton method based on the new proposed class of smoothing functions with ${\theta}{\in}(0,1)$ seems to have better numerical performance than those based on some other important smoothing functions, which also demonstrate that our algorithm is promising.

A HYBRID METHOD FOR NCP WITH $P_0$ FUNCTIONS

  • Zhou, Qian;Ou, Yi-Gui
    • Journal of applied mathematics & informatics
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    • 제29권3_4호
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    • pp.653-668
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    • 2011
  • This paper presents a new hybrid method for solving nonlinear complementarity problems with $P_0$-functions. It can be regarded as a combination of smoothing trust region method with ODE-based method and line search technique. A feature of the proposed method is that at each iteration, a linear system is only solved once to obtain a trial step, thus avoiding solving a trust region subproblem. Another is that when a trial step is not accepted, the method does not resolve the linear system but generates an iterative point whose step-length is defined by a line search. Under some conditions, the method is proven to be globally and superlinearly convergent. Preliminary numerical results indicate that the proposed method is promising.