• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.371-374
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• 2001

The upstream noise level was measured and analysed for the sample HFC networks to HFC subscriber capacity in the HFC network that is only for cable modem services. The upstream bands were measured not only in HFC networks that have accommodated only cable modem subscribers but in CATV networks that have accommodated cable modem and CATV subscribers. The study says that C/N of HFC networks be maintained though the networks have more cable modem subscribers than CATV networks do. This results are being expected to be used as a basis of network design and management of HFC network provider .

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.26-35
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• 1996

In this paper, some fundamental problems concerning RBF(radial-basis-function) networks and approximation of functions are addressed. First, a comprehensive introduction to RBF networks is given with typical RBF networks classified into three classes. Next, sharp conditions are given under which continuous functions of a finite number of real variables can be approximated arbitrarily well by a certain class of RBF networks. Finally, a related result is given concerning the representation of functions in the form of distributed RBF networks.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.708-711
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• 1997

This paper proposes the hybrid algorithm for the optimization of the structure and parameters of the fuzzy neural networks by genetic algorithms (GA) to improve the behaviour and the design of fuzzy neural networks. Fuzzy neural networks have a distinguishing feature in that they can possess the advantage of both neural networks and fuzzy systems. In this way, we can bring the low-level learning and computational power of neural networks into fuzzy systems and also high-level, human like IF-THEN rule thinking and reasoning of fuzzy systems into neural networks. As a result, there are many research works concerning the optimization of the structure and parameters of fuzzy neural networks. In this paper, we propose the hybrid algorithm that can optimize both the structure and parameters of fuzzy neural networks. Numerical example is provided to show the advantages of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.932-940
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• 1999

In this paper, a new neural networks and neural network based sliding mode controller are proposed. The new neural networks are an mor self-recurrent neural networks which use a recursive least squares method for the fast on-line leammg. The error self-recurrent neural networks converge considerably last than the back-prollagation algorithm and have advantage oi bemg less affected by the poor initial weights and learning rate. The controller for suspension system is designed according to sliding mode technique based on new proposed neural networks. In order to adapt shding mode control mnethod, each frame dstance hetween ground and vehcle body is estimated md controller is designed according to estimated neural model. The neural networks based sliding mode controller approves good peiformance throllgh computer sirnulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.338-342
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• 2000

In order to approximate a nonlinear function, wacelet neural networks combining wacelet theory and neural networks have been proposed as an alternative to conventional multi-layered neural networks. wacelet neural networks provide better approximating performance than conventional neural networks. In this paper, an effective method to construct an optimal wavelet neural network is proposed using genetic alogorithm. Genetic Algorithm is used to determine dilationa and translations of wavelet basic functions of wavelet neural networks. Then, these determined dilations dilations and translations, wavelet neural networks are funther trained by back propagation learning algorithm. The effectiveness of the final network is verified thrifigh the approximation result of a nonlinear function and comparison with conventional neural networks.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.169-178
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• 2012

In this paper, we study the advantages of using range extension cooperative transmission (CT) in multi-hop energy harvesting wireless sensor networks (EH-WSNs) from the network layer perspective. EH-WSNs rely on harvested energy, and therefore, if a required service is energy-intensive, the network may not be able to support the service successfully. We show that CT networks that utilize both range extension CT and non-CT routing can successfully support services that cannot be supported by non-CT networks. For a two-hop toy network, we show that range extension CT can provide better services than non-CT. Then, we provide a method of determining the supportable services that can be achieved by using optimal non-CT and CT routing protocols for EH-WSNs. Using our method and network simulations, we justify our claim that CT networks can provide better services than nonCT networks in EH-WSNs.

• ETRI Journal
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• v.33 no.6
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• pp.924-934
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• 2011

Sensor networks play an important role in making the dream of ubiquitous computing a reality. With a variety of applications, sensor networks have the potential to influence everyone's life in the near future. However, there are a number of issues in deployment and exploitation of these networks that must be dealt with for sensor network applications to realize such potential. Localization of the sensor nodes, which is the subject of this paper, is one of the basic problems that must be solved for sensor networks to be effectively used. This paper proposes a probabilistic support vector machine (SVM)-based method to gain a fairly accurate localization of sensor nodes. As opposed to many existing methods, our method assumes almost no extra equipment on the sensor nodes. Our experiments demonstrate that the probabilistic SVM method (PSVM) provides a significant improvement over existing localization methods, particularly in sparse networks and rough environments. In addition, a post processing step for PSVM, called attractive/repulsive potential field localization, is proposed, which provides even more improvement on the accuracy of the sensor node locations.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.669-673
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• 2008

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.

• Journal of the Korean Regional Science Association
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• v.13 no.2
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• pp.55-74
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• 1997

This paper investigates the spatial characteristics of networks, which arise as a firm's strategy to enhance its competitiveness to cope with the changing economic environments characterized by technological changes and increasing competitiveness. The theoretical framework in this study proposes that networks emerge as a firm's strategies to promote its competitiveness through the vertical/horizontal disintegration of the production system. Futhermore, regional industries of networks. The study examines the types of cooperation and the spatial boundary of the computer industry networks in Korea. Questionnaire survey was conducted on 1, 128 computer companies which had more than 10 employees, with 126 questionnaires being used for analysis. In addition, newpaper articles were used to supplement the foregoing work on network characteristics. The review of these articles covers the period from Jan. 1994 to June 1996. Major findings of this study are as follows: The spatial range of cooperative networks varies according to the specific characters of cooperation(R & D, production, and seles). Intralocal networks are being developed in Kangnam and Youido area, the computer industry agglomeration clusres of Seoul. There are the regional differnces in the agents and contents of cooperation. In intra-national R & D and production networks, regional differnces in agglomeratins and non-agglomerations are not detercted. Most networks of this type are found between large firms and small firms. In contrast, foregn R & D and production networks, which are operated mostly by large firms, are found in Kangnam, Youido, and CBD. Intra-national and foreign productino networks are also focused in Kangnam, Youido, and CBD. Small firms are playing an active role in making this type of cooperation possible. In the perspective of localization-globalization, Korean computer industry can be analyzed in two respects: industrial and regional. The localization of small firms and the localization-globalization of large firms' networks are being developed in industrial contexts, while the localization-globalization of agglomerations and the localization of non-agglomerations networks are being developed in regional contexts. As networks for the localization-globalization of industry are growing in agglomerations, interfirm networks could be related to trends in the formation or intensification of industrial agglomerations. industrial agglomeration areas function as a facilitator of localization through subcontracts, intraregional network and interregional network. They also facilitate globalization via foregn networks. In non-agglomeratin areas, localization networks, which are connected with agglomeration areas via subcontracting, interregional R & D. or production cooperation.

• Journal of KIISE:Information Networking
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• v.32 no.2
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• pp.236-243
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• 2005

Most of the existing legacy DSL networks, about 80 million lines world-widely, adopted ‘ATM(Asynchronous Transfer Mode) over DSL’protocol architecture for the effective interworking with the ATM-based regional backbone networks and for the effective support of native ATM-based multimedia application services. Recently, however, the regional backbone networks are moving towards Metro Ethernet networks, instead of the ATM networks, and most of the current multimedia applications are If-based, not native ATM-based. These environmental changes push the architecture of DSL networks to be accordingly changed, and the‘Ethernet over DSL’protocol architecture, instead of existing‘ATM over DSL’, is tried to be applied to the implementation of next generation DSL networks such as VDSL(Very high-rate DSL) . In this paper, we propose two different implementation models for next generation DSL networks in Metro Ethernet backbone environments, respectively EA(Ethernet-to-ATM) implementation model and RE(Ethernet-to-Ethernet) implementation model. And, a comparative analysis focused on the performance and the backward compatability with the legacy DSL networks will be presented.