• Bulletin of the Korean Mathematical Society
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• v.35 no.1
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• pp.157-172
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• 1998

A numerical method is proposed for dynamical systems. We utilize the fact that special matrix exponentials can be exactly evaluated by the intrinsic library functions. Numerical examples are given, which show that the relative error s of the proposed method converge to a small constant and that the method faithfully approximates the dynamics of the nonlinear differential equations.

• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.102-105
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• 2004

A Quadrature phase detector for high-speed delay-locked loop is introduced. The proposed Quadrature phase detector is composed of two nor gates and it determines if the phase difference of two input clocks is 90 degrees or not. The delay locked loop circuit including the Quadrature phase detector is fabricated in a 0.18 um Standard CMOS process and it operates at 5 GHz frequency. The phase error of the delay-locked loop is maximum 2 degrees and the circuits are robust with voltage, temperature variations.

• Communications of the Korean Mathematical Society
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• v.38 no.3
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• pp.901-911
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• 2023

In this paper a generalization of convergent sequences in connection with generalized topologies and filters is given. Additionally, properties such as uniqueness, behavior related to continuous functions are established and notions relative to product spaces.

• ETRI Journal
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• v.37 no.2
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• pp.262-272
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• 2015

In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.

• ETRI Journal
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• v.34 no.5
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• pp.666-673
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• 2012

Non-real-time delivery of stereoscopic video has been considered as a service scenario for 3DTV to overcome the limited bandwidth in the terrestrial digital television system. A hybrid codec combining MPEG-2 and H.264/AVC has been suggested for the compression of stereoscopic video for 3DTV. In this paper, we propose a stereoscopic video coding scheme using adaptive pre-/post-filters (APPF) to improve the quality of 3D video while retaining compatibility with legacy video coding standards. The APPF are applied adaptively to blocks of various sizes determined by the macroblock coding mode and reference frame index. Experiment results show that the proposed method achieves up to 24.86% bit rate savings relative to a hybrid codec of MPEG-2 and H.264/AVC including the inter-view prediction.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.199-206
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• 2015

This study is the convenience Facebook brand fan page users who seek functional, emotional, divided into three levels of symbolic benefits to the brand benefit was to examine whether structurally affect to brand attachment and brand commitment. Results and emotional benefits are found to affect the brand attachment relative to the functional convenience. In addition, the symbolic benefits were to affect brand attachment compared with the functional convenience. But the emotional benefits and symbolic benefits was shown to affect different brand without attachment, brand attachment points have been identified that affect the antecedents of brand engagement.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.1
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• pp.96-99
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• 2016

Generally, bistatic clutter, contrary to the monostatic clutter, has nonlinear structure in Angle-Doppler domain due to the noncooperative motion of the transmitter and the receiver. In this paper, we first simulate the bistatic clutter structure resulting from the relative motion of the transmitter and the receiver and then analyze their relations through the bistatic clutter structure in Angle-Doppler domain. Also, we show the operation condition of the transmitter and the receiver leading to low rank of a covariance matrix of the bistatic clutter.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.238-244
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• 2008

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing. This paper presents gamma neural network(GAM) to improve the dynamics of multilayer network. The GAM network uses the gamma memory kernel in the hidden layer of feedforword multilayer network. The GAM network is evaluated in linear and nonlinear system identification, and compared with feedforword(FNN) and recurrent neural networks(RNN) for the relative comparison of its performance. Experimental results show that the GAM network performs better with respect to the convergence and accuracy, indicating that it can be a more effective network than conventional multilayer networks in system identification.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.45-52
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• 2005

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing. This paper describes system identification using the hybrid neural network, composed of locally(LRNN) and globally recurrent neural networks(GRNN) to improve dynamics of multilayered recurrent networks(RNN). The structure of the hybrid nework combines IIR-MLP as LRNN and Elman RNN as GRNN. The hybrid network is evaluated in linear and nonlinear system identification, and compared with Elman RNN and IIR-MLP networks for the relative comparison of its performance. Simulation results show that the hybrid network performs better with respect to the convergence and accuracy, indicating that it can be a more effective network than conventional multilayered recurrent networks in system identification.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.53-59
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• 2006

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing such as system identification and signal prediction. This paper proposes the gamma neural network(GAM), which uses gamma memory kernel in the hidden layer of feedforward multilayered network, to improve dynamics of networks and then describes nonlinear adaptive prediction using the proposed network as an adaptive filter. The proposed network is evaluated in nonlinear signal prediction and compared with feedforword(FNN) and recurrent neural networks(RNN) for the relative comparison of prediction performance. Simulation results show that the GAM network performs better with respect to the convergence speed and prediction accuracy, indicating that it can be a more effective prediction model than conventional multilayered networks in nonlinear prediction for nonstationary signals.