• Title, Summary, Keyword: Network structure

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Double Network Control of Linear Systems (선형 시스템의 이중 네트워크 제어)

  • Lee, Sin-Ho;Choi, Yoon-Ho;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • pp.1743_1744
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    • 2009
  • In this paper, we propose a double network control approach for linear systems. Generally, there are two network control system structures: the direct structure and the hierarchical structure. Here, the hierarchical structure consists of a main controller and a remote controller. The network delay of the structure only appears in the closed loop between the main controller and the remote system. However, the delay can exist between the remote controller and the actuator. Therefore, we design the double network system with delays between the main controller and the remote system, and the remote controller and the actuator. Finally, we carry out simulations on the linear system to illustrate the effectiveness of the proposed control method.

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Modular Cellular Neural Network Structure for Wave-Computing-Based Image Processing

  • Karami, Mojtaba;Safabakhsh, Reza;Rahmati, Mohammad
    • ETRI Journal
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    • v.35 no.2
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    • pp.207-217
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    • 2013
  • This paper introduces the modular cellular neural network (CNN), which is a new CNN structure constructed from nine one-layer modules with intercellular interactions between different modules. The new network is suitable for implementing many image processing operations. Inputting an image into the modules results in nine outputs. The topographic characteristic of the cell interactions allows the outputs to introduce new properties for image processing tasks. The stability of the system is proven and the performance is evaluated in several image processing applications. Experiment results on texture segmentation show the power of the proposed structure. The performance of the structure in a real edge detection application using the Berkeley dataset BSDS300 is also evaluated.

A Novel Neural Network Compensation Technique for PD-Like Fuzzy Controlled Robot Manipulators (PD 기반의 퍼지제어기로 제어된 로봇의 새로운 신경회로망 보상 제어 기술)

  • Song Deok-Hee;Jung Seul
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.6
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    • pp.524-529
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    • 2005
  • In this paper, a novel neural network compensation technique for PD like fuzzy controlled robot manipulators is presented. A standard PD-like fuzzy controller is designed and used as a main controller for controlling robot manipulators. A neural network controller is added to the reference trajectories to modify input error space so that the system is robust to any change in system parameter variations. It forms a neural-fuzzy control structure and used to compensate for nonlinear effects. The ultimate goal is same as that of the neuro-fuzzy control structure, but this proposed technique modifies the input error not the fuzzy rules. The proposed scheme is tested to control the position of the 3 degrees-of-freedom rotary robot manipulator. Performances are compared with that of other neural network control structure known as the feedback error learning structure that compensates at the control input level.

The social network resource exchange and perception of community resources among rural housewives: on the part of interpersonal resources (농촌주부의 사회관계망, 자원교환, 지역사회자원인지 : 대인적 자원부분을중심으로)

    • Journal of Korean Home Management Association
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    • v.15 no.2
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    • pp.45-58
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    • 1997
  • In the traditional rural community social relationships among the people are the routes of resources. But as industrialization goes on rural community has changed. I wonder that rural housewives have yet the traditional social network structure. This stud purposed to analyze the structure of social network resource exchange and perception of community resources. Results were as follows: 1. In the rural housewife's social network structure network range and depth were affected by family income age of the youngest and farming time. Network boundary was affected by near environmental variables such as community resources and community level of living. 2. Community resources was the most influential variable in the resource exchanged 3. Perception of community resources was affected by network depth and was not by the resource exchange.

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Optimization of Neural Network Structure for the Efficient Bushing Model (효율적인 신경망 부싱모델을 위한 신경망 구성 최적화)

  • Lee, Seung-Kyu;Kim, Kwang-Suk;Sohn, Jeong-Hyun
    • Transactions of the Korean Society of Automotive Engineers
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    • v.15 no.5
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    • pp.48-55
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    • 2007
  • A bushing component of a vehicle suspension system is tested to capture the nonlinear behavior of rubber bushing element using the MTS 3-axes rubber test machine. The results of the tests are used to model the artificial neural network bushing model. The performances from the neural network model usually are dependent on the structure of the neural network. In this paper, maximum error, peak error, root mean square error, and error-to-signal ratio are employed to evaluate the performances of the neural network bushing model. A simple simulation is carried out to show the usefulness of the developed procedure.

An Learning Algorithm to find the Optimized Network Structure in an Incremental Model (점증적 모델에서 최적의 네트워크 구조를 구하기 위한 학습 알고리즘)

  • Lee Jong-Chan;Cho Sang-Yeop
    • Journal of Internet Computing and Services
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    • v.4 no.5
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    • pp.69-76
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    • 2003
  • In this paper we show a new learning algorithm for pattern classification. This algorithm considered a scheme to find a solution to a problem of incremental learning algorithm when the structure becomes too complex by noise patterns included in learning data set. Our approach for this problem uses a pruning method which terminates the learning process with a predefined criterion. In this process, an iterative model with 3 layer feedforward structure is derived from the incremental model by an appropriate manipulations. Notice that this network structure is not full-connected between upper and lower layers. To verify the effectiveness of pruning method, this network is retrained by EBP. From this results, we can find out that the proposed algorithm is effective, as an aspect of a system performence and the node number included in network structure.

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A study on the SCM Activity and Business Performance varied with the Supply Chain Structure (공급사슬구조에 따른 SCM 활동과 경영성과에 관한 연구)

  • Jang Hyeong-Wook;Lee Sang-Shik;Park Byung-Kwon
    • The Journal of Information Systems
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    • v.15 no.2
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    • pp.173-193
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    • 2006
  • This study first conceptualizes and investigates five dimensions of SCM activities, such as organizational capacity, revitalization support collaboration, appraisal and responsibility, and information system activities. Second, this study develops three dimensions of a supply chain structure, and proposes a balanced scorecard (BSC) model in order to measure business performance. And then, this study establishes too research hypotheses as follows: H1. The SCM activities varies with the supply chain structure. H2. The management performance varies with the supply chain structure. In the questionnaire survey for empirical analysis, this study carefully selected 809 of companies in Korea. We conducted a survey by mail and collected 127 data. Out of 127 data we actually used 103 responses for statistical analysis. After conducting statistical analysis, we could find the results as followed: 1) The supply chain structure was classified into three networks through a clustering procedure, such as supply network, conversion network, and distribution network, and these networks were used to testify hypotheses. As a result the effect of SCM activities varies according to three networks and especially, the companies in distribution network were more active than those in supply and conversion networks doing SCM activities. 2) We may conclude that business performance varies with three networks, and distribution network achieves better performance than supply and conversion networks do.

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Generalized Rearrangeable Networks with Recursive Decomposition Structure

  • Kim, Myung-Kyun;Hyunsoo Yoon;Maeng, Seung-Ryoul
    • Journal of Electrical Engineering and information Science
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    • v.2 no.5
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    • pp.121-128
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    • 1997
  • This paper proposes a class of rearrangeable networks, called generalized rearrangeable networks(GRNs). GRNs are obtained from the Benes network by rearranging the connections between states and the switches within each stage. The GRNs constitute all of the rearrangeable networks which have the recursive decomposition structure and can be routed by the outside-in decomposition of permutations as the Bene network. This paper also presents a necessary condition for a network to be a GRN and a network labeling scheme to check if a network satisfies the condition. the general routing algorithm for the GRNs is given by modifying slightly the looping algorithm of the Benes network.

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Visual servoing of robot manipulators using the neural network with optimal structure (최적화된 신경회로망을 이용한 동적물체의 비주얼 서보잉)

  • 김대준;전효병;심귀보
    • 제어로봇시스템학회:학술대회논문집
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    • pp.302-305
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    • 1996
  • This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

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An Analysis of Influence Factor of ROK Military Supply-Network Efficiency by Social Network Analysis (사회연결망분석을 통한 한국군 공급네트워크 구조의 효율성 영향요인 분석)

  • Eom, Jin-Wook;Won, You-Jae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.5
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    • pp.47-55
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    • 2019
  • The army of republic of korea have been continued to transform their logistics support system structure for better efficient logistics support system in preparation for the future environment. Logistics system has supply network structure which is connected by various units and supply network structure received attention as a factor of success of supply network. Many researchers have continuously researched inventory management, transportation or economy factors for supply network, but such a study on the one in military supply network structure analysis is still slower than the study of analysis of other factors until now. In this study, we identify military supply network structure influence factor by application of social network analysis method which is used broadly and analyze co-relationships between supply network structure influence factor and valued APL(average path length) as a criteria of efficiency of military supply network. By this study it has value of military supply network influence factor identification for the better military supply network fabrication.