• 제목/요약/키워드: Iterative SENSE

검색결과 50건 처리시간 0.034초

APPROXIMATING COMMON FIXED POINTS OF ONE-STEP ITERATIVE SCHEME WITH ERROR FOR NON-SELF ASYMPTOTICALLY NONEXPANSIVE IN THE INTERMEDIATE SENSE MAPPINGS

  • Saluja, Gurucharan Singh;Nashine, Hemant Kumar
    • East Asian mathematical journal
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    • 제26권3호
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    • pp.429-440
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    • 2010
  • In this paper, we study a new one-step iterative scheme with error for approximating common fixed points of non-self asymptotically nonexpansive in the intermediate sense mappings in uniformly convex Banach spaces. Also we have proved weak and strong convergence theorems for above said scheme. The results obtained in this paper extend and improve the recent ones, announced by Zhou et al. [27] and many others.

Noor Iterations with Error for Non-Lipschitzian Mappings in Banach Spaces

  • Plubtieng, Somyot;Wangkeeree, Rabian
    • Kyungpook Mathematical Journal
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    • 제46권2호
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    • pp.201-209
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    • 2006
  • Suppose C is a nonempty closed convex subset of a real uniformly convex Banach space X. Let T : $C{\rightarrow}C$ be an asymptotically nonexpansive in the intermediate sense mapping. In this paper we introduced the three-step iterative sequence for such map with error members. Moreover, we prove that, if T is completely continuous then the our iterative sequence converges strongly to a fixed point of T.

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Takagi-Sugeno Fuzzy Model-based Iterative Learning Control Systems: A Two-dimensional System Theory Approach

  • Chu, Jun-Uk;Lee, Yun-Jung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.169.3-169
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    • 2001
  • This paper introduces a new approach to analysis of error convergence for a class of iterative learning control systems. First, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established in the form of T-S fuzzy model. We analysis the error convergence in the sense of induced 2 L -norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative learning controller design problem to guarantee the error convergence can be reduced to linear matrix inequality problems. In comparison with others, our learning algorithm ...

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The Iterated Ritz Method: Basis, implementation and further development

  • Dvornik, Josip;Lazarevic, Damir;Uros, Mario;Novak, Marta Savor
    • Coupled systems mechanics
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    • 제7권6호
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    • pp.755-774
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    • 2018
  • The Ritz method is known as very successful strategy for discretizing continuous problems, but it has never been used for solving systems of algebraic equations. The Iterated Ritz Method (IRM) is a novel iterative solver based on the discretized Ritz procedure applied at each iteration step. With an appropriate choice of coordinate vectors, the method may be efficient in linear, nonlinear and optimization problems. Additionally, some iterative methods can be explained as special cases of this approach, which helps to understand advantages and limitations of these methods and gives motivation for their improvement in sense of IRM. In this paper, some ideas for generation of efficient coordinate vectors are presented. The algorithm was developed and tested independently and then implemented into the open source program FEAP. Method has been successfully applied to displacement based (even ill-conditioned) models of structural engineering practice. With this original approach, a new iterative solution strategy has been opened.

EXTENDED HERMITE-HADAMARD(H-H) AND FEJER'S INEQUALITIES BASED ON GEOMETRICALLY-s-CONVEX FUNCTIONS IN THIRD AND FOURTH SENSE

  • SABIR YASIN;MASNITA MISIRAN;ZURNI OMAR;RABIA LUQMAN
    • Journal of applied mathematics & informatics
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    • 제41권5호
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    • pp.963-972
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    • 2023
  • In this paper, geometrically convex and s-convex functions in third and fourth sense are merged to form (g, s)-convex function. Characterizations of (g, s)-convex function, algebraic and functional properties are presented. In addition, novel functions based on the integral of (g, s)-convex functions in the third sense are created, and inequality relations for these functions are explored and examined under particular conditions. Further, there are also some relationships between (g, s)-convex function and previously defined functions. The (g, s)-convex function and its derivatives will then be used to extend the well-known H-H and Fejer's type inequalities. In order to obtain the previously mentioned conclusions, several special cases from previous literature for extended H-H and Fejer's inequalities are also investigated. The relation between the average (mean) values and newly created H-H and Fejer's inequalities are also examined.

Takagi-Sugeno 퍼지모델에 기반한 반복학습제어 시스템: 이차원 시스템이론을 이용한 접근방법 (Takagi-Sugeno Fuzzy Model-Based Iterative Learning Control Systems: A Two-Dimensional System Theory Approach)

  • 추준욱;이연정;최봉열
    • 제어로봇시스템학회논문지
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    • 제8권5호
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    • pp.385-392
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    • 2002
  • This paper introduces a new approach to analysis of error convergence for a class of iterative teaming control systems. Firstly, a nonlinear plant is represented using a Takagi-Sugeno(T-S) fuzzy model. Then each iterative learning controller is designed for each linear plant in the T-S fuzzy model. From the view point of two-dimensional(2-D) system theory, we transform the proposed learning systems to a 2-D error equation, which is also established if the form of T-S fuzzy model. We analyze the error convergence in the sense of induced L$_2$-norm, where the effects of disturbances and initial conditions on 2-D error are considered. The iterative teaming controller design problem to guarantee the error convergence can be reduced to the linear matrix inequality problem. This method provides a systematic design procedure for iterative teaming controller. A simulation example is given to illustrate the validity of the proposed method.

Feedback-Based Iterative Learning Control for MIMO LTI Systems

  • Doh, Tae-Yong;Ryoo, Jung-Rae
    • International Journal of Control, Automation, and Systems
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    • 제6권2호
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    • pp.269-277
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    • 2008
  • This paper proposes a necessary and sufficient condition of convergence in the $L_2$-norm sense for a feedback-based iterative learning control (ILC) system including a multi-input multi-output (MIMO) linear time-invariant (LTI) plant. It is shown that the convergence conditions for a nominal plant and an uncertain plant are equal to the nominal performance condition and the robust performance condition in the feedback control theory, respectively. Moreover, no additional effort is required to design an iterative learning controller because the performance weighting matrix is used as an iterative learning controller. By proving that the least upper bound of the $L_2$-norm of the remaining tracking error is less than that of the initial tracking error, this paper shows that the iterative learning controller combined with the feedback controller is more effective to reduce the tracking error than only the feedback controller. The validity of the proposed method is verified through computer simulations.

STRONG CONVERGENCE THEOREMS FOR FIXED POINT PROBLEMS OF ASYMPTOTICALLY QUASI-𝜙-NONEXPANSIVE MAPPINGS IN THE INTERMEDIATE SENSE

  • Jeong, Jae Ug
    • Journal of applied mathematics & informatics
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    • 제32권5_6호
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    • pp.621-633
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    • 2014
  • In this paper, we introduce a general iterative algorithm for asymptotically quasi-${\phi}$-nonexpansive mappings in the intermediate sense to have the strong convergence in the framework of Banach spaces. The results presented in the paper improve and extend the corresponding results announced by many authors.

Fast Iterative Image Restoration Algorithm

  • Moon, J.I.;Paik, J.K.
    • Journal of Electrical Engineering and information Science
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    • 제1권2호
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    • pp.67-76
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    • 1996
  • In the present paper we propose two new improved iterative restoration algorithms. One is to accelerate convergence of the steepest descent method using the improved search directions, while the other accelerates convergence by using preconditioners. It is also shown that the proposed preconditioned algorithm can accelerate iteration-adaptive iterative image restoration algorithm. The preconditioner in the proposed algorithm can be implemented by using the FIR filter structure, so it can be applied to practical application with manageable amount of computation. Experimental results of the proposed methods show good perfomance improvement in the sense of both convergence speed and quality of the restored image. Although the proposed methods cannot be directly included in spatially-adaptive restoration, they can be used as pre-processing for iteration-adaptive algorithms.

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디지털 자동초점을 위한 반복적 Unsharp Mask 필터 (Iterative Unsharp Mask Filter for Digital Auto-Focusing)

  • 신정호
    • 대한전자공학회논문지SP
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    • 제47권5호
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    • pp.145-152
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    • 2010
  • 본 논문에서는 초점 열화를 제거하기 위해서 반복적 Unsharp mask (UM) 필터를 이용한 디지털 자동초점 기법을 제안한다. 제안한 디지털 자동초점 기술은 영상열화를 추정하기 위해서 점확산함수를 추정하지 않고 단순한 필터를 사용하기 때문에 계산량이 적은 장점을 갖는다. 본 기법은 반복적 필터 구조로 영상을 복원하기 때문에 사용자의 주관적 기준 및 영상의 객관적 지표를 사용하여 필터링의 반복 회수를 제한할 수 있다. 또한 반복적 UM 기반의 영상개선 방법이 기존의 반복적 영상복원 기술과 등가임을 보인다. 마지막으로 본 논문에서 제안한 알고리듬의 성능평가를 위해서 기존의 영상복원 기반의 디지털 자동초점 기술과의 비교 실험을 수행하였고, 이를 통하여 제안한 디지털 자동초점 기법이 주관적으로나 객관적으로 우수함을 보였다.