• Journal of Institute of Control, Robotics and Systems
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• v.11 no.9
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• pp.781-788
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• 2005

This paper proposes an identification method using a self recurrent wavelet neural network (SRWNN) for dynamic systems. The architecture of the proposed SRWNN is a modified model of the wavelet neural network (WNN). But, unlike the WNN, since a mother wavelet layer of the SRWNN is composed of self-feedback neurons, the SRWNN has the ability to store the past information of the wavelet. Thus, in the proposed identification architecture, the SRWNN is used for identifying nonlinear dynamic systems. The gradient descent method with adaptive teaming rates (ALRs) is applied to 1.am the parameters of the SRWNN identifier (SRWNNI). The ALRs are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of an SRWNNI. Finally, through computer simulations, we demonstrate the effectiveness of the proposed SRWNNI.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1982-1985
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• 2003

Future cellular networks will mainly be driven by, high quality channels, high band with utilization, low power consumption and efficient network management. For a given channel allocation, the capacity and quality of communication of cellular radio systems using CDMA(Code Division Multiple Access) can be increased by using a transmitter power control scheme to combat the near-far problem. Centralized power control schemes or distributed ones to maximize the minimum signal-to-interference in each user of CDMA wireless network have been investigated. This paper has proposed a distributed power control algorithm, which employs an adaptive search scheme, in order to solve quickly the linear systems of equations for power update in CDMA cellular radio systems. The simulation results show that the proposed scheme has faster convergence rate than the typical bang-bang type of distributed power control algorithm, which has been much used as a reference algorithm in IS-95A and W-CDMA communication network.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.73-79
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• 2017

The Convolutional Neural Network (CNN) has shown an excellent performance in computer vision task. Applications of CNN include image classification, object detection in images, autonomous driving, etc. This paper will evaluate the performance of CNN model with ReLU and SELU as activation function. The evaluation will be performed on four different choices of hyperparameter which are initialization method, network configuration, optimization technique, and regularization. We did experiment on each choice of hyperparameter and show how it influences the network convergence and test accuracy. In this experiment, we also discover performance improvement when using SELU as activation function over ReLU.

• Convergence Security Journal
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• v.6 no.1
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• pp.65-74
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• 2006

In this paper, the definition of mobile virtual network operator (MVNO), business situations of operators, regulations, and main benefits are analyzed to discuss the introduction of MVNO system in Korea. In addition to, the analytical hierarchy process (AHP) is performed to study the efficient business model for MVNO under the government's regulation. The three alternatives such as self-regulation, partial-regulation and full refutation are considered for the main criteria of competitiveness activation, investment increment, and economics.

• Convergence Security Journal
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• v.10 no.2
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• pp.51-57
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• 2010

This paper proposes extended trust evaluation mechanism which is able to become the standard of the node selection which provides a better service by using the basic transaction message which occurs from within the mobile Ad-hoc network and the additional transaction message and add confidence value. Furthermore, throughout the simulation shows the efficiency of the proposed trust evaluation mechanism.

• Journal of the Korean Society of Industry Convergence
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• v.14 no.3
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• pp.95-100
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• 2011

The modern society longing for the convenience of up-to-date technology, there are attempts of miniaturization and high reliance of power equipments in the effectiveness aspect of urban area's usage of space while requiring more electrical energy than now. Consequently, paper used to the Neral Network for a forcasting conservation system. A neral network is powerful asta modeling tool that is able to capture and represent complex input/output relationships. The true power and advantage of neral networks lies in their ability to learn these relationships directly from the data being modeled. Traditional linear models are simply inadequate when it comes to modeling data that contains non-linear characteristics. Form results of this study, the Neral Network is will play an important role for insulation diagnosis system of real site GIS and power eqipment using $SF_6$ gas.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.199-203
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• 2011

The wireless sensor network (WSN) based on ad hoc network is applied to vehicle parking guide system without parking guide man at area or building with large scale of parking lots. The optimum number of cluster heads was derived for getting the minimum power consumption as well as time delay. Through the theoretical analysis of power consumption and time delay with the number of cluster heads in wireless sensor network, it was found that there exists the minimum point in the variation of power consumption and time delay according to the number of cluster heads.

• Korean Management Science Review
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• v.32 no.4
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• pp.175-192
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• 2015

Due to the emergence of open innovation driven by development of network service technologies and convergence in ICT service industry, It is necessary for ICT service firms to examine their capabilities for open innovation. The purpose of this paper is to empirically examine determinants affecting open innovation in Korean ICT service industry. In order to analyze, this paper uses logistic and multiple regression models based on survey data of Korean ICT service firms. Estimation results show that external network for collaboration is positive on the technological innovation activity regardless of the innovation type. Specifically, user networks are significant in all types of technology innovation, revealing that it is important to innovation activities of the ICT service firms.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1860-1861
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• 2006

In this paper, we design a robust controller of biped robot system with uncertainties, using recurrent neural network. In our proposed control system, we use the self-recurrent wavelet neural network (SRWNN). The SRWNN makes up for the weak points in wavelet neural network(WNN). While the WNN has fast convergence ability, it dose not have a memory. So the WNN cannot confront unexpected change of the system. However, the SRWNN, having advantage of WNN such as fast convergence, can easily encounter the unexpected change of the system. For stable walking control of biped robot, we use sliding mode control (SMC). Here, uncertainties are predicted by SRWNN. The weights of SRWNN are trained by adaptive laws based on Lyapunov stability theorem. Finally, we carry out computer simulations with a biped robot model to verify the effectiveness of the proposed control system,.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.778-781
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• 2005

In this paper, we describe a development of a Bluetooth Access Point for the WAN connection of home network devices. Especially, users can access the PSTN at home instead of expensive digital cellular network through the AP, using the 'one-phone', which is the Bluetooth enabled cellular phone. The simultaneous benchmark test about telephone service and LAN access service shows the perfect compatibility and reasonable performance of the access point. The one-phone service can become a convergence of wired and wireless communication through the AP.