• Title, Summary, Keyword: Network structure

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A Robust Control with a Neural Network Structure for Uncertain Robot Manipulator

  • Han, Myoung-Chul
    • Journal of Mechanical Science and Technology
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    • v.18 no.11
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    • pp.1916-1922
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    • 2004
  • A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.

Community-based Knowledge Networks: an Australian case study (커뮤니티 기반 지식 네트워크: 호주 사례 연구)

  • Bendle, Lawrence J.
    • Knowledge Management Research
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    • v.12 no.2
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    • pp.69-80
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    • 2011
  • This paper reports on a structural view of a knowledge network comprised of clubs and organisationsexpressly concerned with cultural activities in a regional Australian city. Social network analysis showed an uneven distribution of power, influence, and prominence in the network. The network structure consisted of two modules of vertices clustered around particular categories of creative arts and these modules were linked most frequently by several organisations acting as communication hubs and boundary spanners. The implications of the findings include 'network weaving' for improving the network structure and developing a systemic approach for exploring the structures of social action that form community-based knowledge networks.

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Online Social Network Interactions: A Cross-cultural Comparison of Network Structure on McDonald's Facebook Sites between Taiwan and USA

  • Chang, Hui-Jung
    • International Journal of Knowledge Content Development & Technology
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    • v.7 no.4
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    • pp.5-26
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    • 2017
  • A cross-cultural comparison of social networking structure on McDonald's Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald's Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald's Facebook fan network has more fans, while Taiwan's McDonald's Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

The Industry Structure Change in China and The Study Related of Building Korea-China's New Network (중국의 산업구조변화와 한중간 새로운 네트워크 구축에 관한 연구)

  • Kim, Kyung-Jong;Seo, Jong-Hyen
    • Journal of the Korea Safety Management & Science
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    • v.13 no.3
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    • pp.175-182
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    • 2011
  • The purpose of this article is to suggest what is the desirable direction of economic relationship between Korea and China. The economic relationship between countries is based on how the present network is. As the economic relationship between countries grows, the network between countries will expand. In the past, the economic relationship between Korea and China is cooperative one from the viewpoint of international division of labor. Korean industries was focused on the value-added and mid-advanced technology products, while Chinese was focused on the labor-intensive products. As the China's economy grows for more than thirty years, there is a great change in China's economic policies and environment. China's industry structure is moving from the labor-intensive industry to technology-oriented industry. China's exports to the global market is increasing very fast, and China's domestic market is also growing. The change in Chinese industries' structure bring about severe competition in the global market. The expanding China's domestic market is also good opportunity as the new market in the world. The change in China's industrial structure needs for Korea to establish the 'New Network" between two countries. Korea has to grab the new opportunities in the China's domestic market and find new cooperative network with the products and industries.

Design and Performance Analysis of A Novel P2P-SIP Architecture for Network-based Mobility Support in Intelligent Home Networks (지능형 홈네트워크에서 네트워크 기반의 이동성 지원을 위한 P2P-SIP 구조의 설계 및 성능분석)

  • Kim, SeungWon;Jeong, JongPil
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.7
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    • pp.293-302
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    • 2013
  • Home network providers have many worries about providing home network services with an expandable, reliable, flexible and low-cost structure according to the expanding market environment. The existing client-server system has various problems such as complexity and high costs in providing home network services. In this paper we propose the P2P-SIP structure. P2P communication terminal supporting access of distributed resources provides functions which the existing SIP-based network devices have. Because diverse terminals in a home network access through networks, also, partitioning network domains with home gateways to manage, and applying the network-based PMIPv6(Proxy Mobile IPv6) technology considering mobility of terminals would help to have a more efficient home network structure. Especially, the proposed P2P-SIP structure proves itself as a very efficient structure to have an outstanding expandability among different home networks in a region, and to reduce maintenance costs.

Modelling of a Shipboard Stabilized Satellite Antenna System Using an Optimal Neural Network Structure (최적 구조 신경 회로망을 이용한 선박용 안정화 위성 안테나 시스템의 모델링)

  • Kim, Min-Jung;Hwang, Seung-Wook
    • Journal of Navigation and Port Research
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    • v.28 no.5
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    • pp.435-441
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    • 2004
  • This paper deals with modelling and identification of a shipboard stabilized satellite antenna system using the optimal neural network structure. It is difficult for shipboard satellite antenna system to control and identification because of their approximating ability of nonlinear function So it is important to design the neural network with optimal structure for minimum error and fast response time. In this paper, a neural network structure using genetic algorithm is optimized And genetic algorithm is also used for identifying a shipboard satellite antenna system It is noticed that the optimal neural network structure actually describes the real movement of ship well. Through practical test, the optimal neural network structure is shown to be effective for modelling the shipboard satellite antenna system.

A Study on Polynomial Neural Networks for Stabilized Deep Networks Structure (안정화된 딥 네트워크 구조를 위한 다항식 신경회로망의 연구)

  • Jeon, Pil-Han;Kim, Eun-Hu;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.12
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    • pp.1772-1781
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    • 2017
  • In this study, the design methodology for alleviating the overfitting problem of Polynomial Neural Networks(PNN) is realized with the aid of two kinds techniques such as L2 regularization and Sum of Squared Coefficients (SSC). The PNN is widely used as a kind of mathematical modeling methods such as the identification of linear system by input/output data and the regression analysis modeling method for prediction problem. PNN is an algorithm that obtains preferred network structure by generating consecutive layers as well as nodes by using a multivariate polynomial subexpression. It has much fewer nodes and more flexible adaptability than existing neural network algorithms. However, such algorithms lead to overfitting problems due to noise sensitivity as well as excessive trainning while generation of successive network layers. To alleviate such overfitting problem and also effectively design its ensuing deep network structure, two techniques are introduced. That is we use the two techniques of both SSC(Sum of Squared Coefficients) and $L_2$ regularization for consecutive generation of each layer's nodes as well as each layer in order to construct the deep PNN structure. The technique of $L_2$ regularization is used for the minimum coefficient estimation by adding penalty term to cost function. $L_2$ regularization is a kind of representative methods of reducing the influence of noise by flattening the solution space and also lessening coefficient size. The technique for the SSC is implemented for the minimization of Sum of Squared Coefficients of polynomial instead of using the square of errors. In the sequel, the overfitting problem of the deep PNN structure is stabilized by the proposed method. This study leads to the possibility of deep network structure design as well as big data processing and also the superiority of the network performance through experiments is shown.

A study on interrelation between the structure of a Plant and the str neural network emulator and the learning rate (플랜트구조와 신경망에뮬레이터의 구조 및 학습시간과의 관계)

  • Pae, Chang-Han;Lee, Kwang-Won
    • Proceedings of the KIEE Conference
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    • pp.386-389
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    • 1997
  • Error-backpropagation has been used in the bulk of Practical applications for neural networks. While an emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. There is, however, no concrete theoretical results about the structure of a plant and the structure of a multilayered neural network and the learning rate. The paper investigates the relation between structure of a plant and a multilayered network and learning rate. Simulation study shows that the plant signal with a short period and a fast sam time is preferable for learning of the network emulator.

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Phoneme Recognition Using Frequency State Neural Network (주파수 상태 신경 회로망을 이용한 음소 인식)

  • Lee, Jun-Mo;Hwang, Yeong-Soo;Kim, Seong-Jong;Shin, In-Chul
    • The Journal of the Acoustical Society of Korea
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    • v.13 no.4
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    • pp.12-19
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    • 1994
  • This paper reports a new structure for phoneme recognition neural network. The proposed neural network is able to deal with the structure of the frequency bands as well as the temporal structure of phonemic features which used in the conventional TSNN. We trained this neural network using the phonetics (아, 이, 오, ㅅ, ㅊ, ㅍ, ㄱ, ㅇ, ㄹ, ㅁ) and the phoneme recognition of this neural network was a little better than those of conventional TDNN and TSNN using only temporal structure of phonemic features.

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Connection method on pre-installed bridge monitoring system for bridge structure safety network (교량시설물 안전관리 네트워크 구축을 위한 기존 시스템 연계방안 연구)

  • Park, Ki-Tae;Lee, Woo-Sang;Joo, Bong-Chul;Hwang, Yoon-Koog
    • 한국방재학회:학술대회논문집
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    • pp.469-472
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    • 2008
  • In general, structures in service gradually lose original performance according to time due to initial defects in design and construction, or exposure to unfavorable external conditions such as repeated loading or deteriorating environment, and in extreme cases, may collapse in large disaster. Therefore, in order to maintain the serviceability of structures at optimal level, advanced structure measuring system which can inform optimal time point and method of maintenance is required in addition to accurate prediction of residual life the structure by periodic inspection. To guarantee the safety level of bridge structure and to prevent from disaster, the integration of safety network for bridge structures are needed. Therefore in this study, to enhance the effectiveness of safety network for bridge, the connection methodologies between safety network and pre-installed bridge monitoring system are investigated.

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