• 한국지능시스템학회논문지
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• 제8권6호
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• pp.58-69
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• 1998

This paper introduces a novel neuro-fuzzy system based on the polynomial fuzzy neural network(PFNN) architecture. The PFNN consists of a set of if-then rules with appropriate membership functions whose parameters are optimized via a hybrid genetic algorithm. A polynomial neural network is employed in the defuzzification scheme to improve output performance and to select appropriate rules. A performance criterion for model selection, based on the Group Method of DAta Handling is defined to overcome the overfitting problem in the modeling procedure. The hybrid genetic optimization method, which combines a genetic algorithm and the Simplex method, is developed to increase performance even if the length of a chromosome is reduced. A novel coding scheme is presented to describe fuzzy systems for a dynamic search rang in th GA. For a performance assessment of the PFNN inference system, three well-known problems are used for comparison with other methods. The results of these comparisons show that the PFNN inference system outperforms the other methods while it exhibits exceptional robustness characteristics.

• 전력전자학회논문지
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• 제5권6호
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• pp.544-551
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• 2000

In this paper, 3-phase hybrid series active power filter for compensate current harmonics, voltage drop and unbalanced voltage in the network presented. The proposed system is implemented with a space vector modulation voltage source inverter and a high pass filter connected in parallel to the power system. Here the load is six-pulses thyristor rectifier. The phase angle detected in order to generation reference voltage at load terminal is synchronized with the positive sequence component of the unbalanced source by using symmetrical component transformation. The proposed system has an function harmonic isolation between source and load, voltage regulation, and unbalance compensation. Therefore, what the power system is improved quality, the source current is maintained as a nearly sinusoidal waveform and the load voltage is regulated with a rated voltage regardless of the source variation condition. To verify the validity of the proposed compensating system, the computer simulation and experiment are carried out.

• ETRI Journal
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• 제35권4호
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• pp.655-665
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• 2013

Hybrid digital multimedia broadcasting (DMB) is a next-generation mobile TV system that combines broadcasting and wireless communication networks and can provide various high-quality multimedia services. However, if a system adheres to the current standard of transmitting the DMB content in the form of MPEG2-TS through wireless networks, it results in a burden on the network due to low transmission efficiency. The reasons for the low transmission efficiency are as follows. First, due to its constant bitrate characteristic, DMB MPEG2-TS includes a considerable amount of needless information, such as NULL packets and stuffing bytes. Second, due to the inflexibility of the Real-time Transport Protocol (RTP) standard, one cannot fully utilize the maximum transmission unit of the network when converting MPEG2-TS to RTP stream for transmission. This paper proposes a new transmission scheme that resolves these problems. Experiment results show that the proposed scheme improves data bitrate transmission efficiency by 8% to 36%, compared to the standard scheme, in the streaming of various real-DMB contents.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.928-931
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• 2002

Network based intrusion detection system is a computer network security tool. In this paper, we present an intrusion detection system based on Self-Organizing Maps (SOM) and Resilient Propagation Neural Network (RPROP) for visualizing and classifying intrusion and normal patterns. We introduce a cluster matching equation for finding principal associated components in component planes. We apply data from The Third International Knowledge Discovery and Data Mining Tools Competition (KDD cup'99) for training and testing our prototype. From our experimental results with different network data, our scheme archives more than 90 percent detection rate, and less than 5 percent false alarm rate in one SYN flooding and two port scanning attack types.

• 산업경영시스템학회지
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• 제28권3호
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• pp.133-141
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• 2005

The previous research has been mainly focused on individual technology of voice recognition, voice synthesis, translation, and bone transmission technical. Recently, commercial models have been produced using aforementioned technologies. In this research, a new automated translation support system concept has been proposed by combining established technology of bone transmission and wireless system. The proposed system has following three major components. First, the hybrid system consist of headset, bone transmission and other technologies will recognize user's voice. Second, computer recognized voice (using small server attached to the user) of the user will be converted into digital signal. Then it will be translated into other user's language by translation algorithm. Third, the translated language will be wirelessly transmitted to the other party. The transmitted signal will be converted into voice in the other party's computer using the hybrid system. This hybrid system will transmit the clear message regardless of the noise level in the environment or user's hearing ability. By using the network technology, communication between users can also be clearly transmitted despite the distance.

• 전자공학회논문지
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• 제53권4호
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• pp.27-34
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• 2016

철도 차량은 일렬로 연결되는 구조적 특수성이 있으므로 네트워크 토폴로지를 구성하는 경우에서도 이를 고려하여야 한다. 또한 차량 내의 장치 간 연결에서의 토폴로지와 차량 간 연결에서의 토폴로지를 구분하여야 한다. 차량 간 연결에 있어서 기존의 링, 스타, 데이지체인, 버스 등의 토폴로지 대신 이를 조합한 하이브리드 토폴로지가 제안되었다. 이는 일렬로 연결된 철도 차량을 적절한 수의 그룹으로 묶고 그룹 내에서는 스타 네트워크 토폴로지로 구성하고 그룹 간 연결은 데이지체인 네트워크 토폴로지로 구성하는 방식이다. 이를 통해 하이브리드 토폴로지는 스타 토폴로지에 비해 차량 간 연결에 필요한 케이블의 수를 절감하고도 적절한 전송 속도를 유지할 수 있다. 하이브리드 토폴로지는 스타와 데이지 체인 두 가지 토폴로지를 절충하는 방식이므로 각각의 장점을 잘 활용할 수 있도록 그룹 내 차량의 수를 적절히 선정하는 것이 중요하다. 본 논문에서는 철도차량에서 최적의 하이브리드 네트워크 토폴로지를 구하는 것을 목적으로 한다. 이를 위해 차량 별로 데이터 생성 크기와 생성 주기가 동일하다는 가정 하에 차량 간 연결에서의 최대 케이블 수와 전송 속도에 대하여 각각 가중치를 별도로 두고 가중치 별로 전체 차량 수에 따른 최적의 그룹 내 차량의 수를 도출한다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.809-812
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• 1999

The pendulum is a SIMO(Single-input multi-output) system that both angle of pendulum and position of cart controlled simultaneously by one actuator. In this paper, propose a hybrid neuro-controller to apply to pendulum system. We design the conventional optimal controller and the neural network as a identifier, which can identify the uncertainty of plant not modeled, respectively. Then we combine them into a novel controller, with a structure that the error between plant and identifier is added in conventional optimal control input Finally, the paper shows the validity of the proposed controller through computer simulations and experiments.

• Journal of Electrical Engineering and Technology
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• 제3권4호
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• pp.468-475
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• 2008

This paper presents a method for estimating the transient stability status of the power system using radial basis function(RBF) neural network with a fast hybrid training approach. A normalized transient energy margin(${\Delta}V_n$) has been obtained by the potential energy boundary surface(PEBS) method along with a time-domain simulation technique, and is used as an output of the RBF neural network. The RBF neural network is then trained to map the operating conditions of the power system to the ${\Delta}V_n$, which provides a measure of the transient stability of the power system. The proposed approach has been successfully applied to the 10-machine 39-bus New England test system, and the results are given.

• ETRI Journal
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• 제38권5호
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• pp.838-846
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• 2016

The objective of digital broadcasting has evolved from providing a plain video service to offering a realistic visual experience. Technologies such as 3DTV and UHDTV have been suggested to achieve this new objective by providing an immersive and stereoscopic visual experience. However, owing to the high bandwidth requirements of such services, the broadcasting industry has faced a challenge to find a new transport mechanism for overcoming the bandwidth limitation. The standardization organizations, the Advanced Television Systems Committee, Digital Video Broadcasting, and Telecommunications Technology Association, have been working on the integration of broadcasting and a broadband network (IP) to resolve the bandwidth issue of realistic video services. This paper introduces a frame-level timeline synchronization and transport system target decoder model for providing a stable 3DTV service over a hybrid network. The experimental results indicate that the proposed technologies can be successfully adopted as a reference model in a broadcast-broadband hybrid 3DTV service and other IP-associated hybrid broadcasting services.

• 정보처리학회논문지B
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• 제9B권4호
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• pp.429-436
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• 2002

인공 신경망을 실제적인 응용 분야에 적용하기 위하여 하드웨어 시스템으로 구현하는 것이 필요하다. 하드웨어로 구현하는 방법에는 현재 하이브리드 VLSI 신경망 칩으로 구현하는 것이 가장 유망하다. 이미 학습된 신경망을 하이브리드 신경망 칩을 사용하여 구현하는 경우 뉴런 출력과 가중치 값의 양자화 과정이 필수적이다. 이러한 과정은 신경망의 출력층 뉴런의 이미 학습된 출력에 비해 왜곡을 야기한다. 본 논문에서는 이러한 신경망의 출력 왜곡에 대한 통계적 특성을 자세하게 분석하였다. 분석 결과는 신경망의 출력 왜곡을 줄이기 위해서는 입력 벡터의 정규화와 가중치 값들이 작아야 한다는 사실을 보여 주었다. 시계열 데이터에 대한 실험 결과는 분석 결과를 고려하여 학습된 신경망들의 경우 실제로 뉴런 출력 및 가중치 값의 양자화로 인한 출력층 뉴런의 출력 왜곡이 상당히 줄어들 수 있음을 명확히 보여 주었다.