• 기술사
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• 제24권2호
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• pp.127-136
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• 1991

The communication transmission engineering plays the most important role in electrical communications engineering. Recently, it has been making remarkable progress as an infrastructure supporting informationaged society. Specially, the start of television conference and service of high speed digital transmission can be said it is announcing a raising curtain of high speed broad band age. Together with high speed broad band service needs a capacity as much as several or several hundred times of telephone with one circuit, various kinds of service forms are anticipated to emerge, it is anticipated to give a big impact to the way of future communications network. At present, telecommunication network is transforming telephone voice information by analog technology into a flexible higher system disposable of a variety of information such as pictures or data other than telephone by the introduction of digital technology. Consequently, the development of the hereafter for the following respective technologies is desired.

• 한국정보처리학회논문지
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• 제1권1호
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• pp.99-104
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• 1994

본 논문은 LSI의 물리적 레이아웃 설계시 다량의 패턴 데이타를 고속으로 처리할 수 있는 새로운 2차원 병렬처리 방법을 제안한고 메모리와 프로세서간에 데이타를 양방향으로 고속 전송 하는 스위칭 네트워크를 설계하였다.이스위칭 네트워크를 VHDL 설계 시스템을 이용하여 시뮬레이션하여 그 동작을 확인하였다.

• 한국항행학회논문지
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• 제22권5호
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• pp.429-435
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• 2018

레이다 시스템의 경우, 타겟의 거리와 속도를 추출하기 위해 FFT (fast Fourier transform) 연산이 필수적으로 요구되며, 실시간 구현을 위해 고속으로 동작하는 FFT 프로세서의 설계가 필요하다. 고속 FFT 프로세서를 위한 하드웨어 구조로 완전 셔플 네트워크 (perfect shuffle network) 구조가 적합하며, 특히 초고속 연산을 위해 radix-4 기반의 이중 완전 셔플 네트워크 (twice perfect shuffle network) 구조가 가장 적절하고 볼 수 있다. 더불어, 다양한 속도 해상도를 요구하는 레이다 응용을 고려할 때, FFT 프로세서는 가변길이 FFT 연산을 지원할 필요가 있다. 이에 본 논문에서는 8~1024 포인트의 가변 길이 연산을 지원하는 이중 완전 셔플 네트워크 기반의 FFT 알고리즘을 제안하였으며, 이의 하드웨어 구조 설계 및 구현 결과를 제시한다. 제안된 FFT 프로세서는 HDL (hardware description language)을 활용하여 RTL (register transfer level) 설계가 수행되었으며, $0.65{\mu}m$ CMOS 공정을 활용하여 논리 합성한 결과, 총 3,293K개의 논리 게이트로 구현 가능함을 확인 할 수 있었다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2009년도 춘계학술대회 논문집 특별세미나,특별/일반세션
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• pp.527-532
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• 2009

Recently, Interior Permanent Magnet Machine(IPM) is widely used for traction motor in the high speed train. Due to the high efficiency and high power density of the IPM, it has lots of heat sources such as iron loss and copper loss. These heat sources can cause the demagnetization of permanent magnet, losses in output power and even irreversible defect of the IPM. To prevent the power loss caused by heat sources, the accurate thermal analysis has to be carried out. For the thermal analysis of the IPM, the thermal network is designed for this traction motor. The thermal analysis has executed at rated speed operation. The result of thermal network analysis can be used for the IPM design process.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.958-959
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• 2008

This paper is proposed a high performance speed control of the Interior Permanent Magnet Synchronous Motor through the Neural Network SV-PWM. SV-PWM is controlled using Neural Network control. SV-PWM can be maximum used maximum dc link voltage and is excellent control method due to characteristic to reducing harmonic more than others. Neural Network control has a advantage which can be robustly controlled. Simulation results are presented to show the validity of the proposed algorithm.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.2021-2026
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• 2008

Recently, a high speed rail consists of many train coaches and power cars. For keeping the reliable train communication system with train coaches and power cars, train uses the OSI model(Open Systems Interconnection Basic Reference Model) and KTX(Korea Train eXpress) only uses the Physical to Transport layer of OSI model. This paper describes the analysis of CLNP(Connectionless Network Protocol) and ES-IS(End System to Intermediate System) protocols used in KTX for the network layer. CLNP is used to send data to other system and ES-IS protocol is used to route and send information between end systems and intermediate systems. Also this paper presents the protocol parsing program and implementation of Network layer.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.233-236
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• 2005

Our country compares with advanced nations by supply of super high speed network and information communication infra construction has gone well very. Many people by extension of on-line transaction and various internet services can exchange, or get information easily in this environment. But, virus or poisonous information used to Cyber terror such as hacking was included within such a lot of information and such poisonous information are threatening national security as well as individual's private life. There were always security and speed among a lot of items to consider networks equipment from these circumstance to now when develop and install in trade-off relation. In this paper, we present a high speed VPN Acceleration Board(VPN-AB) that balances both speed and security requirements of high speed network environment. Our VPN-AB supports two VPN protocols, IPsec and SSL. The protocols have a many cryptographic algorithms, DES, 3DES, AES, MD5, and SHA-1, etc.. The acceleration board process data packets into the system with In-line mode. So it is possible that VPN-AB processes inbound and outbound packets by 10Gbps. We use Nitrox-II CN2560 security processor VPN-AB is designed using that supports many hardware security modules and two SPI-4.2 interfaces to design VPN-AB.

• 전기학회논문지P
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• 제58권3호
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• pp.249-256
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive learning mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control (FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN, FLC and ANN controller.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.53-55
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• 2006

This paper presents self tuning PI controller of IPMSM drive using neural network. NNPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain 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.