• Journal of the Korean Mathematical Society
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• v.53 no.5
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• pp.1133-1148
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• 2016

In this paper, we first discuss a representation of solutions to the initial value problem and the initial-boundary value problem for discrete evolution equations $${\sum\limits^l_{n=0}}c_n{\partial}^n_tu(x,t)-{\rho}(x){\Delta}_{\omega}u(x,t)=H(x,t)$$, defined on networks, i.e. on weighted graphs. Secondly, we show that the weight of each link of networks can be uniquely identified by using their Dirichlet data and Neumann data on the boundary, under a monotonicity condition on their weights.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.585-592
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• 1996

This paper analyzes the impact of digitalization on networks in Seoul Metropolitan Area by considering facility investment together with operatinng costs. A stepwise evolution method toward a digitalized double-homming architecture is proposed to accommodate most efficiently with existing analog-oriented networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3907-3923
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• 2020

An enhanced irregular repetition slotted ALOHA (IRSA) protocol is proposed by using polarization characteristic of satellite link and MIMO detection in low earth orbit (LEO) satellite networks, which is dubbed polarized MIMO IRSA (PM-IRSA). In the proposed scheme, one or two packets in one slot can be decoded by employing polarized MIMO detection, and more than two collided packets in multiple slots which can construct the virtual MIMO model can be decoded by the MIMO detection algorithm. The performance of the proposed scheme is analyzed with the density evolution (DE) approach and the degree distribution is optimized to maximize the system throughput by using a differential evolution. Numerical results certify our analysis and show that the normalized throughput of the proposed PM-IRSA can achieve 1.89 bits/symbol.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.413-416
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• 1997

Recently, dynamic recurrent neural networks(DRNN) for identification of nonlinear dynamic systems have been researched extensively. In general, dynamic backpropagation was used to adjust the weights of neural networks. But, this method requires many complex calculations and has the possibility of falling into a local minimum. So, we propose a new approach to identify nonlinear dynamic systems using DRNN. In order to adjust the weights of neurons, we use evolution strategies, which is a method used to solve an optimal problem having many local minimums. DRNN trained by evolution strategies with mutation as the main operator can act as a plant emulator. And the fitness function of evolution strategies is based on the difference of the plant's outputs and DRNN's outputs. Thus, this new approach at identifying nonlinear dynamic system, when applied to the simulation of a two-link robot manipulator, demonstrates the performance and efficiency of this proposed approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5328-5346
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• 2016

An optimal power control algorithm based on convex optimization is proposed for base stations in long term evolution networks. An objective function was formulated to maximize the proportional fairness of the networks. The optimal value of the objective function was obtained using convex optimization and distributed methods based on the path loss model between the base station and users. Field tests on live networks were conducted to evaluate the performance of the proposed algorithm. The experimental results verified that, in a multi-cell multi-user scenario, the proposed algorithm increases system throughputs, proportional fairness, and energy efficiency by 9, 1.31 and 20.2 %, respectively, compared to the conventional fixed power allocation method.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.131-138
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• 1998

In this paper, we investigate the direction of LAN evolution. We focus rather on the philosophical changes than on the advances of technologies. In terms of topology, channel structure, and medium access control, we categorize major local area networks widely used in the past. We then investigate new directions in the concept and advances in the technology of local area networks. The idea of collapsed backbone is shown to be the most fundamental factor influencing the evolution of local area networks. Asynchronous Transfer Mode that is radically different form the existing LAN technology is now actively applied to LAN. In order to compete with ATM, conventional LANs should evolve to support quality of service for multimedia application

• IE interfaces
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• v.18 no.3
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• pp.277-287
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• 2005

In this paper, we deal with a new techno-economic modeling and analysis for optical access networks. In deploying the fiber-to-the-home (FTTH) architecture, network planner needs to consider the following techno-economic issues: when do we need to upgrade existing local access network to FTTH network? how much do we invest to maximize profit? In order to answer these techno-economic questions, we need to consider the impact of emerging technologies and business environment. Toward this end, we develop a new techno-economic modeling to deal with the inherent complexity of technology evolution and cost economics. In particular, the new modeling approach provides us with an techno-economic analysis of technology alternatives such as ethernet passive optical network (E-PON) and wavelength division multiplex passive optical network (WDM-PON). In this analysis, we focus on the impact of critical factors such as the cost characteristic of proposed architecture and digital subscriber line (DSL) subscriber's churn-in to FTTH service and churn-out. We develop mixed integer-programming models for finding the evolution path of local access networks to broadband network architectures.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.920-924
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• 2005

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the environment. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.31-36
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• 2008

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the enviromuent. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• International journal of advanced smart convergence
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• v.2 no.1
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• pp.24-26
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• 2013

In the process of a mobile network evolution to the All-IP, it is inevitable to experience a transient period embracing both circuit and packet based data traffics. At the stage of those hybrid networks, it is important to build them in an efficient manner in terms of resource utilization which is closely related to the overall system operation cost. Especially, the multimedia telephony is one of the essential services in the advanced packet based mobile networks. In this paper an effective method of system operation is proposed for building up the multimedia telephony service while the legacy network co-exists. The proposed solution is based on the careful investigation of the usage pattern of the multimedia services in the evolving networks. This method is also expected to be a useful guideline for the network resource planning.