• 한국IT서비스학회지
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• 제14권3호
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• pp.85-97
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• 2015

The information and communications construction business has the characteristics of an infrastructure industry and responsibility for the construction and maintenance of all ICT infrastructures. With the recent proliferation of the smart convergence of various industries based on ICT infrastructure, the role of the information and communications construction business has been highlighted to accommodate the convergence and implementation environment in construction and medical industries. Therefore, this paper seeks policy measures to establish the new role of the information and communications business under the rapidly developing smart convergence environment and the priorities of policy measures to strengthen the capability of the information and communications business using a quantitative model. The analysis result suggests that the difference in importance of each policy measure should be considered in order to execute effectively the policy of promoting the information and communications construction business. Given the constraint of limited budget, policy priorities include the development of new markets, and establishment of incentive for new technology. This study is significant for its theoretical contribution, being the first quantitative approach to policy priorities for the promotion of information and communications construction business under the smart convertgence environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2065-2069
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• 2004

This paper presents an adaptive equalizer using finite impulse response (FIR) filter and least-mean square (LMS) algorithm. Herein, the variable step-size technique (VSLMS) for compensating the amplitude of chrominance signal is utilized. The proposed equalizer can be enhanced and compressed the chrominance signal at color subcarrier. The LMS algorithm employed in simplicity structure but gives slow convergence speed. Thus, the variable step-size is very attractive algorithm due to its computational efficiencies and the speed of convergence is improved. In addition, experimental results are carried out by using the modulated 20T sine squared test signal. It is shown here that the adaptive equalizer can be equalized the amplitude chrominance distortion in color television transmission without relative delay distortion.

• 융합보안논문지
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• 제16권6_2호
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• pp.23-32
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• 2016

급격한 정보통신기술의 발달은 경찰에게 새로운 도전이자 기회가 되고 있다. 이 연구는 국내외 치안분야의 ICT기술 활용사례를 검토하고, 그 시사점을 확인하는 것을 목적으로 한다. 이를 위해 정보통신기술 활용에 관한 경찰활동의 근거이론으로 정보주도 경찰활동(intelligence-led policing), 예측적 경찰활동(predictive policing), 증거기반 경찰활동(evidence-based policing)의 개념에 대해 소개하였다. 또, 빅데이터 기반 범죄분석과 예측기술 활용방안과 경찰의 정보통신체계 및 지휘통제기술의 고도화방안에 대해 논의하였다. 이 연구를 통해 확인한 시사점으로 (1) 기본데이터의 확보, (2) 활용가능한 통합D/B의 구축, (3) 정책결정자의 활용성 증대, (4) 유관기관 사이의 교류협력, (5) 전문가집단의 양성, (6) 통합 D/B구축의 법적 근거와 실무적 가이드라인 마련을 제안한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 추계학술발표논문집 (상)
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• pp.305-308
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• 2003

본 논문은 토너먼트 선택을 사용한 Deceptive Problem에서 최적 해(optimum)를 찾으면서 수렴(Convergence)속도를 향상시키기 위한 최적의 조건을 찾고자 한다. 이를 위해 적합도가 높은 염색체(cromosome)를 다음 세대로 전달하면서 동시에 적합도가 낮은 염색체에 대해서도 적정 수준 전달되게 하였다. 또한 기존의 여러 선택기법 중 가장 일반적으로 사용되는 토너먼트 선택 기법의 문제점을 고찰하고, 제안 방법으로 최적도 및 수렴속도를 모의 실험을 통해 비교 및 분석한다. 실험 결과로부터 제안 방법에 대한 수렴속도의 경향을 고찰하였다.

• 제어로봇시스템학회논문지
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• 제9권11호
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• pp.917-924
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• 2003

Recurrent neural networks have been successfully applied to communications channel equalization. Major disadvantages of gradient-based learning algorithms commonly employed to train recurrent neural networks are slow convergence rates and long training sequences required for satisfactory performance. In a high-speed communications system, fast convergence speed and short training symbols are essential. We propose decision feedback equalizers using a recurrent neural network trained with Kalman filtering algorithms. The main features of the proposed recurrent neural equalizers, utilizing extended Kalman filter (EKF) and unscented Kalman filter (UKF), are fast convergence rates and good performance using relatively short training symbols. Experimental results for two time-varying channels are presented to evaluate the performance of the proposed approaches over a conventional recurrent neural equalizer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.445-445
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• 2000

This paper proposes the MIMO indirect adaptive fuzzy controller to control the two-link manipulators. The input-output linearization technique, equivalent control input plus integral term, augmented error model and recursive least square adaptive law are used fer the controller. The linear type of fuzzifier-defuzzifier fuzzy logic system used for nonlinear function makes easy to farm the error model and able to follow the adaptive system approach. Such that control approach, the control system is not required joint speed and accerelation measurement and easy to implement and tune. The simulation results showed that the proposed controller has good control performance, stability, very small tracking error, decoupling, fast convergence, robust to parameter variation and load.

• Journal of Communications and Networks
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• 제18권3호
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• pp.411-419
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• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.

• 정보과학회지
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• 제28권7호
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• pp.44-51
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• 2010

• 정보과학회지
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• 제31권3호
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• pp.10-21
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• 2013

• 정보과학회지
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• 제31권2호
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• pp.54-62
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• 2013