• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.210-212
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• 2012

하이브리드 스마트 홈 클라우드 플랫폼/서비스 기술은 가정 내 외 클라우드와 연계하여 실시간으로 수정되는 다양한 콘텐츠, 응용 프로그램, 스마트 가전, 개인 생활 정보들을 융합 관리 함으로써 멀티미디어, 어플리케이션, 스마트 가전 등을 통하여 다양한 스마트 융복합 서비스를 제공해 줄 수 있는 기술이다. 이에 본 논문은 데이터의 프라이버시, 안정성, 보안성, 종속화등 Public Cloud에 대한 거부반응을 해소하기 위해 개인 또는 흠단위로 스마트 콘텐츠를 서로 공유할수 있는 댁내 Private 클라우드와 다양한 스마트 홈 서비스를 제공하는 사업자 및 소셜 그룹간의 공유가 가능한 댁 외 Public 클라우드와 연계하여, 실시간으로 수집되는 다양한 콘텐츠, 용용 프로그램, 스마트 가전, 개인 생활 정보들을 통합 관리하고, 서비스 가상화 기술을 이용하여 다양한 경량화 스마트 가전(Thin/Zero Client)에 동시 적용 가능한 "하이브리드 홈 클라우드 단말 서버 플랫폼 기술을 연구하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.4
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• pp.340-351
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• 1988

Up to now, hybrid torque/position control of robot manipulator have been researched under the assumption that link mass and/or load are known. This paper proposes a torque and position control method under unknown mass of links or load of a robot manipulator and the method extend control in joint space to control in operational space. In the method, known parameters are used to estimate unknown parameter. We illustrate the theory with some simulations and show that the result is effective.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1839-1842
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• 2002

Ad hoc networks are characterized by multi- hop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. In this paper, we proposed a new technique to adjust the zone radius by concentrating the changes of network traffic in a particular direction, which we refer to as AZRP. We demonstrate that even though ZRP and AZRP share a similar hybrid routing behavior, the differences in the protocol mechanics can lead to significant performance differentials. We discuss the algorithm and report on the performance of AZRP scheme, and compare it to the ZRP routing protocol. Our results indicate clearly that AZRP outperforms ZRP by reducing significantly the number of route query messages. And thereby increases the efficiency of the network load.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.17-19
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• 2005

This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using learning mechanism-fuzzy neural network(LM-FNN) and artificial neural network (ANN) control. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid Intelligent control

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2374-2376
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• 2000

In this paper, we propose an indirect vector control method using Adaptive Neuro-Fuzzy Inference System (ANFIS) parameter estimator. It estimates the rotor time constant when the indirect vector control of induction motor is applied. We use the stator current error that is difference between the current command and estimated current calculated from terminal voltage and current. And two induced current estimate equations are used in training ANFIS.The estimator is trained by the hybrid learning algorithm. Simulation results shows good performance under load disturbance and motor parameter variations.

• ETRI Journal
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• v.37 no.3
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• pp.502-511
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• 2015

Intrusion detection plays a key role in detecting attacks over networks, and due to the increasing usage of Internet services, several security threats arise. Though an intrusion detection system (IDS) detects attacks efficiently, it also generates a large number of false alerts, which makes it difficult for a system administrator to identify attacks. This paper proposes automatic fuzzy rule generation combined with a Wiener filter to identify attacks. Further, to optimize the results, simplified swarm optimization is used. After training a large dataset, various fuzzy rules are generated automatically for testing, and a Wiener filter is used to filter out attacks that act as noisy data, which improves the accuracy of the detection. By combining automatic fuzzy rule generation with a Wiener filter, an IDS can handle intrusion detection more efficiently. Experimental results, which are based on collected live network data, are discussed and show that the proposed method provides a competitively high detection rate and a reduced false alarm rate in comparison with other existing machine learning techniques.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.71-78
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• 1997

In this paper, a new neural network training algorithm will be devised for function approximator with good generalization characteristics and tested with the time series prediction problem using santaFe competition data sets. To enhance the generalization ability a constraint term of hidden neuraon activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. A hybrid learning algorithm of the error-back propagation and Hebbian learning algorithm with weight decay constraint will be naturally developed by the steepest decent algorithm minimizing the proposed cost function without much increase of computational requriements.

• Journal of the Korean Institute of Telematics and Electronics
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• v.21 no.2
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• pp.24-28
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• 1984

A new type of digital echo canceler for two-wire digital transmission is presented. The new principle estimates an echo signal by use of the arithmetic means estimate for each transmitted data pattern, which leads to relatively simple hardware. The principle is compared with adaptive digital filter methods through theoretical analysis and computer simulation. The results show that the proposed method has fast convergence property with respect to its hardware simplicity and that the convergence time is independent of echo level. Quantization effects are also analyzed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.117-122
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• 1998

A servo system requires faster and more accurate dynamic reponses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, designed on the Fuzzy controller with a various series rules, width of membership functions. And also it was showed to have the excellent adaptive performances against disturbances and the usefulness of this controller from the results of simulations.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.8
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• pp.395-401
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• 2005

This paper presents Hybrid PI(HBPI) controller of induction motor drive using fuzzy control. In general, PI controllers used in computer numerically controlled machines process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gam tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.