• 제목/요약/키워드: iterative process

검색결과 652건 처리시간 0.033초

Revised Iterative Goal Programming Using Sparsity Technique on Microcomputer

  • Gen, Mitsuo;Ida, Kenichi;Lee, Sang M.
    • 한국경영과학회지
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    • 제10권1호
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    • pp.14-30
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    • 1985
  • Recently, multiple criteria decision making has been well established as a practical approach to seek a satisfactory solution to a decision making problem. Goal programming is one of the most powerful MCDM tools with satisfying operational assumptions that reflect the actual decision making process in real-world situations. In this paper we propose an efficient method implemented on a microcomputer for solving linear goal programming problems. It is an iterative revised goal simplex method using the sparsity technique. We design as interactive software package for microcomputers based on this method. From some computational experiences, we can state that the revised iterative goal simplex method using the sparsity technique is the most efficient one for microcomputer for solving goal programming problems.

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Iterative SAR Segmentation by Fuzzy Hit-or-Miss and Homogeneity Index

  • Intajag Sathit;Chitwong Sakreya;Tipsuwanporn Vittaya
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.111-114
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    • 2004
  • Object-based segmentation is the first essential step for image processing applications. Recently, SAR (Synthetic Aperture Radar) segmentation techniques have been developed, however not enough to preserve the significant information contained in the small regions of the images. The proposed method is to partition an SAR image into homogeneous regions by using a fuzzy hit-or-miss operator with an inherent spatial transformation, which endows to preserve the small regions. In our algorithm, an iterative segmentation technique is formulated as a consequential process. Then, each time in iterating, hypothesis testing is used to evaluate the quality of the segmented regions with a homogeneity index. The segmentation algorithm is unsupervised and employed few parameters, most of which can be calculated from the input data. This comparative study indicates that the new iterative segmentation algorithm provides acceptable results as seen in the tested examples of satellite images.

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로봇 매니퓰레이터의 반복 학습 제어 (Iterative learning control of robot manipulators)

  • 문정호;도태용;정명진
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.470-473
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    • 1996
  • This paper presents an iterative learning control scheme for industrial manipulators. Based upon the frequency-domain analysis, the input update law of the learning controller is given together with a sufficient condition for the convergence of the iterative process in the frequency domain. The proposed learning control scheme is structurally simple and computationally efficient since it is independent joint control depending only on locally measured variables and it does not involve the computation of complicated nonlinear manipulator dynamics. Moreover, it is capable of canceling the unmodeled dynamics of the manipulator without even the parametric model. Several important aspects of the learning scheme inherent in the frequency-domain design are discussed and the control performance is demonstrated through computer simulations.

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Performance of Iterative Equalizer for ISI channel

  • Nguyen, Quoc Kien;Jeon, Taehyun
    • International journal of advanced smart convergence
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    • 제9권3호
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    • pp.141-144
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    • 2020
  • Iterative decision feedback equalizer (IDFE) is a recursive equalization technique that can help to achieve an additional performance gain for the system by combining iterative channel decoding and interference cancellation. In a single carrier-based system, the intersymbol interference (ISI) is a critical problem that must be resolved since it causes frequency selective fading. Based on the idea of sharing the estimated information in the process of iteration, IDFE is considered as an efficient solution to improve the robustness of the system performance on the ISI channel. In this paper, the IDFE is applied on single carrier FDMA (SC-FDMA) system to evaluate the performance under ISI channel. The simulation results illustrate that IDFE helps to improve the performance of the SC-FDMA system, especially with long delay spread channels.

Low-Complexity Non-Iterative Soft-Decision BCH Decoder Architecture for WBAN Applications

  • Jung, Boseok;Kim, Taesung;Lee, Hanho
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제16권4호
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    • pp.488-496
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    • 2016
  • This paper presents a low-complexity non-iterative soft-decision Bose-Chaudhuri-Hocquenghem (SD-BCH) decoder architecture and design technique for wireless body area networks (WBANs). A SD-BCH decoder with test syndrome computation, a syndrome calculator, Chien search and metric check, and error location decision is proposed. The proposed SD-BCH decoder not only uses test syndromes, but also does not have an iteration process. The proposed SD-BCH decoder provides a 0.75~1 dB coding gain compared to a hard-decision BCH (HD-BCH) decoder, and almost similar coding gain compared to a conventional SD-BCH decoder. The proposed SD-BCH (63, 51) decoder was designed and implemented using 90-nm CMOS standard cell technology. Synthesis results show that the proposed non-iterative SD-BCH decoder using a serial structure can lead to a 75% reduction in hardware complexity and a clock speed 3.8 times faster than a conventional SD-BCH decoder.

화상의 반복 복원 처리 (An Iterative Image Restoration)

  • 이태홍
    • 한국통신학회논문지
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    • 제17권8호
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    • pp.891-897
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    • 1992
  • 본 논문은 일반반복 화상 처리가 화상 전체에 화사의 정보와 상관없이 일률적인 방법으로 적용함으로서 생기는 비 효율성을 고려하여 처리하는 화소의 주변 화상 정보를 이용하여 평면 부분과 윤곽 부부느이 처리회수를 달리하여 주므로서 시각적인 효과와 동시에 처리 시간을 단축하는 국부 반복 복원 방법을 제안하였다. 국부 반복 복원 방법은 일반 반복, 복원 알고리즘을 적용하여 윤곽 부분을 집중 복원하고 평면 부분은 복원없이 통과하는 방법으로, 여기에 사용된 일반 반복 알고리즘이 수렴하면 국분 반복 복원도 수렴하게 됨을 이용하였다. 각각 처리된 화상,MSE, 처리 시간등을 비교하여 그 효율성을 확인하였다.

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AUTOMATIC ADJUSTMENT OF DISCREPANCIES BETWEEN LIDAR DATA STRIPS - USING THE CONTOUR TREE AND ITERATIVE CLOSEST POINT ALGORITHM

  • Lee, Jae-Bin;Han, Dong-Yeob;Yu, Ki-Yun;Kim, Yong-Il
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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    • pp.500-503
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    • 2006
  • To adjust the discrepancy between Light Detection and Ranging (LIDAR) strips, previous researches generally have been conducted using conjugate features, which are called feature-based approaches. However, irrespective of the type of features used, the adjustment process relies upon the existence of suitable conjugate features within the overlapping area and the ability of employed methods to detect and extract the features. These limitations make the process complex and sometimes limit the applicability of developed methodologies because of a lack of suitable features in overlapping areas. To address these drawbacks, this paper presents a methodology using area-based algorithms. This approach is based on the scheme that discrepancies make complex the local height variations of LIDAR data whithin overlapping area. This scheme can be helpful to determine an appropriate transformation for adjustment in the way that minimizes the geographical complexity. During the process, the contour tree (CT) was used to represent the geological characteristics of LIDAR points in overlapping area and the Iterative Closest Points (ICP) algorithm was applied to automatically determine parameters of transformation. After transformation, discrepancies were measured again and the results were evaluated statistically. This research provides a robust methodology without restrictions involved in methods that employ conjugate features. Our method also makes the overall adjustment process generally applicable and automated.

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뉴로제어 및 반복학습제어 기법을 결합한 미지 비선형시스템의 적응학습제어 (Adaptive Learning Control fo rUnknown Monlinear Systems by Combining Neuro Control and Iterative Learning Control)

  • 최진영;박현주
    • 한국지능시스템학회논문지
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    • 제8권3호
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    • pp.9-15
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    • 1998
  • 본 논문은 뉴로제어 및 반복학습 제어기법에 기반한 미지의 비선형시스템의 적응학습제어 방법을 제안한다. 제안된 제어 시스템에서 반복학습제어기는 새로운 기준 궤적에 대해 시스템의 출력이 원하는 궤적으로 정확히 수렴하도록 하는 적응과 단기간 제어정보를 기억하는 기능을 수행한다. 상대차수만 알고 있는 미지 시스템에 대한 박복학습 법칙이 학습이득은 신경회로망을 이용하여 추정된다. 반복학습제어기에 의해 습득된 제어정보는 장기메모리에 기반한 앞먹임 뉴로제어기로 이전되어 누적기억됨으로써 과거에 겸험된 기준 궤적에 대해서는 신속하게 추종할 수 있도록 한다. 2자유도 매니퓰레이터에 적용하여 제안된 기법의 타당성을 검증한다.

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MZ세대 소비자의 패션상품 구매의사결정여정의 반복순환모델 (Iterative Cyclic Model of Generation MZ's Consumer Purchase Decision Journey for a Fashion Product)

  • 이정우;김미영
    • 한국의류학회지
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    • 제46권4호
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    • pp.638-656
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    • 2022
  • This study aimed to identify characteristics of Generation MZ's consumer purchase decision journey to develop the new fashion CDJ model. The initial stage was affected by habit, online community, social media, aesthetics, circumstantial need, and proxy. In the search and consideration stage, mobile channels were used actively. In the active search and evaluation stage, online media, experiential data, and personal information were employed. In the purchase stage, zoomers took plenty of time in search and evaluation before spending, contrary to millennials who made their purchases more quickly. In the post-purchase experience stage, zoomers actively displayed follow-up behaviors depending on their satisfaction, such as retaining or deleting the app. While, millennials did not turn away from the store or brand, but followed up on their purchases even when they had an unsatisfactory experience. Based on the characteristics of CDJ, iterative cycle CDJ models were developed. Zoomers CDJ model was presented as a search loop that consists of the search and evaluation process, in which information accumulates, and a purchase loop in which the actual purchase occurs. The iterative cycle CDJ model was presented connected to the loyalty loop as the main section, which is accelerated in millennials' CDJ model.

순차적 실험계획법과 인공신경망을 이용한 제한조건이 없는 문제의 최적화 알고리즘 개발 (Development of Optimization Algorithm for Unconstrained Problems Using the Sequential Design of Experiments and Artificial Neural Network)

  • 이정환;서명원
    • 대한기계학회논문집A
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    • 제32권3호
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    • pp.258-266
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    • 2008
  • The conventional approximate optimization method, which uses the statistical design of experiments(DOE) and response surface method(RSM), can derive an approximated optimum results through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. The purpose of this study is to propose a new technique, which is called a sequential design of experiments(SDOE), to reduce a trial and error procedure and to find an appropriate condition for using artificial neural network(ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently. The suggested algorithm has been applied to various mathematical examples and a structural problem.