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6th International Conference on Nanotechnology for Instrumentation and Measurement (NanofIM)

作者： Koteras, Dariusz Tomczuk, Bronislaw Waindok, Andrzej Opole Univ Technol Dept Elect Engn & Mechatron Opole Poland

ISBN: (纸本)9781665407007

The prediction and measurement verification of power losses in modern solid ferromagnetic cores operating at medium frequency has been described. The cores are made of nanostructures. After three-dimensional field analysis in the above-mentioned cores, the integral parameters of the field were determined. They differ from the catalog ones. Manufacturers do not provide the values of electrical conductivity and magnetic permeability in a wide range of the flux density values and operating frequencies. Particularly, this applies the electrical conductivities of the solid core, which are necessary for correct determination of eddy current losses. The original implicit iterative algorithm for calculation of the conductivity values under given operating frequencies was developed and presented. The calculated magnetic core losses have been tested for such solid materials as the magnetically soft composite (SMC) called Somaloy and for a ferrite. Good compliance of the calculated hysteresis losses and the eddy current ones with the measured values was obtained.

关键词： modern solid magnetic materials energy losses prediction eddy current losses hysteresis losses 3D field analysis finite element method (FEM) implicit iterative algorithm Somaloy powder ferrites

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implicit iterative algorithms with a tuning parameter for discrete stochastic Lyapunov matrix equations

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IET CONTROL THEORY AND APPLICATIONS 2017年第10期11卷 1554-1560页

作者： Zhang, Ying Wu, Ai-Guo Shao, Chun-Tao Harbin Inst Technol Shenzhen Grad Sch Shenzhen 518055 Peoples R China Harbin Inst Technol Dept Control Sci & Engn Weihai 264209 Peoples R China

An implicit iterative algorithm is established for solving a class of Lyapunov matrix equations appearing in the discrete-time stochastic systems with multiplicative noise. This algorithm contains a tuning parameter which can be appropriately chosen such that it has better convergence performance. Some convergence conditions have been derived for the proposed iterative algorithm, and for a special case an approach is given to choose the optimal tuning parameter such that the algorithm has the best convergence performance. In addition, the properties of boundedness and monotonicity of the proposed algorithm are also investigated when the corresponding stochastic system is asymptotically mean-square stable.

关键词： iterative methods discrete time systems stochastic systems Lyapunov matrix equations convergence of numerical methods asymptotic stability mean square error methods implicit iterative algorithm discrete-time stochastic Lyapunov matrix equations multiplicative noise convergence performance optimal tuning parameter boundedness properties monotonicity properties asymptotically mean-square stable stochastic system

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An implicit iterative algorithm with errors for two families of generalized asymptotically nonexpansive mappings

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FIXED POINT THEORY AND APPLICATIONS 2011年第1期2011卷 1-17页

作者： Agarwal, Ravi P. Qin, Xiaolong Kang, Shin Min Gyeongsang Natl Univ Dept Math Jinju 660701 South Korea Gyeongsang Natl Univ RINS Jinju 660701 South Korea Texas A&I Univ Dept Math Kingsville TX 78363 USA N China Univ Water Resources & Elect Power Sch Math & Informat Sci Zhengzhou 450011 Peoples R China

In this paper, an implicit iterative algorithm with errors is considered for two families of generalized asymptotically nonexpansive mappings. Strong and weak convergence theorems of common fixed points are established based on the implicit iterative algorithm. Mathematics Subject Classification (2000) 47H09 center dot 47H10 center dot 47J25.

关键词： Asymptotically nonexpansive mapping common fixed point implicit iterative algorithm generalized asymptotically nonexpansive mapping

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Data-driven policy iteration algorithm for optimal control of continuous-time Ito stochastic systems with Markovian jumps

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IET CONTROL THEORY AND APPLICATIONS 2016年第12期10卷 1431-1439页

作者： Song, Jun He, Shuping Liu, Fei Niu, Yugang Ding, Zhengtao East China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai 200237 Peoples R China Anhui Univ Sch Elect Engn & Automat Hefei 230601 Peoples R China Jiangnan Univ Inst Automat Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China Univ Manchester Sch Elect & Elect Engn Control Syst Ctr Sackville St Bldg Manchester M13 9PL Lancs England

This studies the infinite horizon optimal control problem for a class of continuous-time systems subjected to multiplicative noises and Markovian jumps by using a data-driven policy iteration algorithm. The optimal control problem is equivalent to solve a stochastic coupled algebraic Riccatic equation (CARE). An off-line iteration algorithm is first established to converge the solutions of the stochastic CARE, which is generalised from an implicit iterative algorithm. By applying subsystems transformation (ST) technique, the off-line iterative algorithm is decoupled into N parallel Kleinman's iterative equations. To learn the solution of the stochastic CARE from N decomposed linear subsystems data, an ST-based data-driven policy iteration algorithm is proposed and the convergence is proved. Finally, a numerical example is given to illustrate the effectiveness and applicability of the proposed two iterative algorithms.

关键词： stochastic systems continuous time systems iterative methods Markov processes convergence of numerical methods Riccati equations transforms optimal control ST-based data-driven policy iteration algorithm infinite horizon optimal control problem continuous-time Ito stochastic systems Markovian jumps multiplicative noises stochastic coupled algebraic Riccatic equation stochastic CARE offline iteration algorithm implicit iterative algorithm subsystems transformation technique parallel Kleinman iterative equations

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Some results on parallel iterative algorithms for strictly pseudocontractive mappings

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JOURNAL OF INEQUALITIES AND APPLICATIONS 2013年第1期2013卷 1-10页

作者： Yang, Xiaoye Qing, Yuan Zhang, Mingliang Tianjin Univ Dept Math Renai Coll Tianjin 301636 Peoples R China Hangzhou Normal Univ Dept Math Hangzhou Zhejiang Peoples R China Henan Univ Dept Math Kaifeng Peoples R China

In this paper, a parallel iterative algorithm with mixed errors is investigated. Strong and weak convergence theorems of common fixed points of a finite family of strictly pseudocontractive mappings are established in... 详细信息

关键词： implicit iterative algorithm fixed point pseudocontractive mapping strictly pseudocontractive mapping

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HYBRID STEEPEST-DESCENT METHODS FOR TRIPLE HIERARCHICAL VARIATIONAL INEQUALITIES

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TAIWANESE JOURNAL OF MATHEMATICS 2013年第4期17卷 1441-1472页

作者： Ceng, Lu-Chuan Wen, Ching-Feng Shanghai Normal Univ Dept Math Shanghai 200234 Peoples R China Sci Comp Key Lab Shanghai Univ Shanghai 200234 Peoples R China Kaohsiung Med Univ Ctr Fundamental Sci Kaohsiung 807 Taiwan

In this paper, we consider a triple hierarchical variational inequality defined over the common solution set of minimization and mixed equilibrium problems. Combining the hybrid steepest-descent method, viscosity approximation method and averaged mapping approach to the gradient-projection algorithm, we propose two iterative methods: implicit one and explicit one, to compute the approximate solutions of our problem. The convergence analysis of the sequences generated by the proposed methods is also established.

关键词： Triple hierarchical variational inequality Minimization problem Mixed equilibrium problem implicit iterative algorithm Explicit iterative algorithm Averaged mapping approach

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Convergence theorems for common fixed points of asymptotically quasi-nonexpansive mappings in convex metric spaces

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APPLIED MATHEMATICS AND COMPUTATION 2012年第9期218卷 4860-4866页

作者： Yildirim, Isa Khan, Safeer Hussain Ataturk Univ Dept Math Fac Sci TR-25240 Erzurum Turkey Qatar Univ Dept Math Stat & Phys Doha 2713 Qatar

In this paper, we consider an implicit iteration process to approximate the common fixed points of two finite families of asymptotically quasi-nonexpansive mappings in convex metric spaces. As a consequence of our result, we obtain some related convergence theorems. Our results generalize some recent results of Khan and Ahmed [4], Khan et al. [6], Sun [12], Wittmann [14] and Xu and Ori [15]. (C) 2011 Elsevier Inc. All rights reserved.

关键词： implicit iterative algorithm Asymptotically quasi-nonexpansive mappings Common fixed point Convex metric space

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Weak and Strong Convergence of an implicit Iteration Process in Uniformly Convex Banach Spaces

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NUMERICAL FUNCTIONAL ANALYSIS AND OPTIMIZATION 2011年第6期32卷 682-694页

作者： Yildirim, Isa Ozdemir, Murat Ataturk Univ Dept Math Fac Sci TR-25240 Erzurum Turkey

The purpose of this article is to introduce an implicit iteration process for approximating common fixed points of three finite families nonexpansive mappings and to prove weak and strong convergence theorems in unifo... 详细信息

关键词： Condition (A') implicit iterative algorithm Nonexpansive mappings Semicompact

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A new one-step implicit iterative process for common fixed points of two asymptotically nonexpansive mappings in Banach spaces

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EXPOSITIONES MATHEMATICAE 2011年第2期29卷 240-251页

作者： Yildirim, Isa Khan, Safeer Hussain Ataturk Univ Fac Sci Dept Math TR-25240 Erzurum Turkey Qatar Univ Dept Math Stat & Phys Doha 2713 Qatar

The purpose of this paper is to introduce an implicit iteration process for approximating common fixed points of two finite families of asymptotically nonexpansive mappings {T-j}(j=1)(N) and {Sj}(j=1)(N) in Banach spaces and to prove weak and strong convergence theorems. The results presented in this paper improve and extend the corresponding results of Chang et al. (2006) [3]. Chidume and Shahzad (2005) [4], Guo and Cho (2008) [8], Qin et al. [10], Sun (2003) [13], Xu and On (2001) [14], Zhao et al. (2008) [15], Zhao and Wang (2009) [16], Zhou and Chang (2002) [17], Zhou et al. (2006) [18]. (C) 2011 Elsevier GmbH. All rights reserved.

关键词： implicit iterative algorithm Asymptotically nonexpansive mapping Opial condition Semicompact Weak and strong convergence

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Strong convergence theorems for strongly continuous semigroups of pseudocontractions

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APPLIED MATHEMATICS LETTERS 2011年第11期24卷 1845-1848页

作者： Agarwal, Ravi P. Qin, Xiaolong Kang, Shin Min Gyeongsang Natl Univ Dept Math Jinju 660701 South Korea Gyeongsang Natl Univ RINS Jinju 660701 South Korea Florida Inst Technol Dept Math Sci Melbourne FL 32901 USA King Fahd Univ Petr & Minerals Dept Math & Stat Dhahran 31261 Saudi Arabia N China Univ Water Resources & Elect Power Sch Math & Informat Sci Zhengzhou 450011 Peoples R China

In this work, strongly continuous semigroups of pseudocontractions are studied based on an implicit iterative algorithm. Strong convergence theorems of fixed points are obtained in an arbitrary Banach space. (C) 2011 ... 详细信息

关键词： Nonexpansive mapping Common fixed point implicit iterative algorithm Pseudocontraction

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