• Journal of Institute of Control, Robotics and Systems
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• v.8 no.5
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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.

• Coupled systems mechanics
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• v.4 no.3
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• pp.263-277
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• 2015

This paper presents a coupled FEM-BEM strategy for the numerical analysis of elastodynamic problems where infinite-domain models and complex heterogeneous media are involved, rendering a configuration in which neither the Finite Element Method (FEM) nor the Boundary Element Method (BEM) is most appropriate for the numerical analysis. In this case, the coupling of these methodologies is recommended, allowing exploring their respective advantages. Here, frequency domain analyses are focused and an iterative FEM-BEM coupling technique is considered. In this iterative coupling, each sub-domain of the model is solved separately, and the variables at the common interfaces are iteratively updated, until convergence is achieved. A relaxation parameter is introduced into the coupling algorithm and an expression for its optimal value is deduced. The iterative FEM-BEM coupling technique allows independent discretizations to be efficiently employed for both finite and boundary element methods, without any requirement of matching nodes at the common interfaces. In addition, it leads to smaller and better-conditioned systems of equations (different solvers, suitable for each sub-domain, may be employed), which do not need to be treated (inverted, triangularized etc.) at each iterative step, providing an accurate and efficient methodology.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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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.

• The Research Journal of the Costume Culture
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• v.28 no.6
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• pp.890-911
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• 2020

This study proposed a base framework for creating sustainable designs with textile production waste and unused neckties with the "design thinking" approach, which is an iterative process. It aimed to set an example of how fashion designers can plan and manage their clothing design processes in a more sustainable way by recycling textile production scraps and unused neckties into unique clothing pieces with the upcycling method. Unused neckties and upholstery scraps were turned into skirts, blouses, and dresses by using creative techniques in line with current fashion trends. In addition, the five-stage iterative design process followed was explained, and the way in which the waste textile materials gained value by being converted into unique garments was discussed in terms of the user and the designer. Through the study, it was observed that the smallest amount of textile waste can be transformed into upcycled clothing via the iterative process, and original, value-added products enjoyed by consumers can be created. In addition, it was observed that the design thinking approach improves the understanding of the context of the problem, creativity in the generation of insights and solutions, skills to materialize those solutions through iterative prototyping, and the ability to combine these factors. Promising ideas to help designers develop recycling strategies were also provided.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4350-4356
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• 2023

Radiation detection systems working at high count rates suffer from the overlapping of their output electric pulses, known as pulse pile-up phenomenon, resulting in spectrum distortion and degradation of the energy resolution. Pulse tail extrapolation is a pile-up correction method which tries to restore the shifted baseline of a piled-up pulse by extrapolating the overlapped part of its preceding pulse. This needs a mathematical model which is almost always nonlinear, fitted usually by a nonlinear least squares (NLS) technique. NLS is an iterative, potentially time-consuming method. The main idea of the present study is to replace the NLS technique by an integration-based non-iterative method (NIM) for pulse tail extrapolation by an exponential model. The idea of linear extrapolation, as another non-iterative method, is also investigated. Analysis of experimental data of a NaI(Tl) radiation detector shows that the proposed non-iterative method is able to provide a corrected spectrum quite similar with the NLS method, with a dramatically reduced computation time and complexity of the algorithm. The linear extrapolation approach suffers from a poor energy resolution and throughput rate in comparison with NIM and NLS techniques, but provides the shortest computation time.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.20-24
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• 2009

Objective: In this study, the differences between two reconstruction methods were analyzed by comparing image uniformity and contrast according to Iteration and Subset, which were altered through the Iterative method and True X method, used in Siemens' PET/CT studies. Methods: The Phantom images were obtained by exposure for two minutes per one bed. To determine the image uniformity, the Coefficient of variance was used. Also, in order to compare the contrast value, we measured and analyzed the ratio of the SUV mean of Phantom image's hot spheres and the background. Results: Under the same reconstruction conditions (Iteration and Subset) of CV, the Iterative method was higher than the True X method. In the comparison of the SUV mean ratio of the background and hot sphere, the True X method had a closer rate than the Iterative method. Conclusion: The newly developed True X reconstruction method is better than the previously used Iterative method in terms of uniformity and contrast. However, the date for this study was only obtained using the Phantom device. In order to obtain more accurate and useful information from the experiment, further research should be conducted. Also, it is necessary to find the appropriate standards for Iteration and Subset for further experimentation.

• Proceedings of the Optical Society of Korea Conference
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• 2001.08a
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• pp.80-81
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• 2001

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.4
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• pp.390-403
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• 2017

Smoothed Particle Hydrodynamics (SPH) method has a good adaptability for the simulation of free surface flow problems. There are two forms of SPH. One is weak compressible SPH and the other one is incompressible SPH (ISPH). Compared with the former one, ISPH method performs better in many cases. ISPH based on Rankine source solution can perform better than traditional ISPH, as it can use larger stepping length by avoiding the second order derivative in pressure Poisson equation. However, ISPH_R method needs to solve the sparse linear matrix for pressure Poisson equation, which is one of the most expensive parts during one time stepping calculation. Iterative methods are normally used for solving Poisson equation with large particle numbers. However, there are many iterative methods available and the question for using which one is still open. In this paper, three iterative methods, CGS, Bi-CGstab and GMRES are compared, which are suitable and typical for large unsymmetrical sparse matrix solutions. According to the numerical tests on different cases, still water test, dam breaking, violent tank sloshing, solitary wave slamming, the GMRES method is more efficient than CGS and Bi-CGstab for ISPH method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.534-540
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• 1993

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algrithms need a special perfect position sensor or a priori information about error sources, while ours does not. To our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterative learning algorithm does not have the drawbacks of the existing iterative learning control theories. To be more specific, our algorithm learns a uncertain function inself rather than its special time-trajectory and does not request the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• ETRI Journal
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• v.30 no.6
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• pp.807-817
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• 2008

We present a low-density parity-check (LDPC)-based, threaded layered space-time-frequency system with emphasis on the iterative receiver design. First, the unbiased minimum mean-squared-error iterative-tree-search (U-MMSE-ITS) detector, which is known to be one of the most efficient multi-input multi-output (MIMO) detectors available, is improved by augmentation of the partial-length paths and by the addition of one-bit complement sequences. Compared with the U-MMSE-ITS detector, the improved detector provides better detection performance with lower complexity. Furthermore, the improved detector is robust to arbitrary MIMO channels and to any antenna configurations. Second, based on the structure of the iterative receiver, we present a low-complexity belief-propagation (BP) decoding algorithm for LDPC-codes. This BP decoder not only has low computing complexity but also converges very fast (5 iterations is sufficient). With the efficient receiver employing the improved detector and the low-complexity BP decoder, the proposed system is a promising solution to high-data-rate transmission over selective-fading channels.