• 방송공학회논문지
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• 제16권2호
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• pp.360-371
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• 2011

T-DMB 하이브리드 데이터 서비스는 서비스를 구성하는 장면 기술 정보와 객체 기술 정보를 방송망 이외의 전송 경로를 통해 분산 전송할 수 있도록 구성하는 하이브리드 BIFS 기술을 이용하여 기존 T-DMB 수신기와의 역호환성을 보장하면서 새로운 데이터 서비스를 제공한다. 본 논문에서는 하이브리드 BIFS 기술을 이용하여 분산 전송이 가능한 BIFS를 구성하기 위한 하이브리드 서비스 저작 프레임워크의 구현 결과와 이를 이용한 실험 결과를 소개한다. 하이브리드 서비스 저작 프레임워크는 서비스 생성 시스템, 서비스 관리 시스템, 콘텐츠 제공 시스템 등으로 구성되며, 통합된 하이브리드 서비스를 저작하는 것은 물론 이를 방송망으로 전송되는 데이터와 무선 통신망을 통해 전송되는 개인맞춤형 데이터로 분할하여 생성하고 관리하는 기능을 제공한다. 이 서비스 프레임워크를 통해 구현된 콘텐츠는 기존 수신기와의 역호환성을 보장하면서 새로운 개인맞춤형 데이터 서비스 구현이 가능함을 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.473-493
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• 2019

5G vehicular communication is one of key enablers in next generation intelligent transportation system (ITS), that require ultra-reliable and low latency communication (URLLC). To meet this requirement, a new hybrid vehicular network structure which supports both centralized network structure and distributed structure is proposed in this paper. Based on the proposed network structure, a new vehicular network utility model considering the latency and reliability in vehicular networks is developed based on Euclidean norm theory. Building on the Pareto improvement theory in economics, a vehicular network uplink optimization algorithm is proposed to optimize the uplink utility of vehicles on the roads. Simulation results show that the proposed scheme can significantly improve the uplink vehicular network utility in vehicular networks to meet the URLLC requirements.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

• 한국통신학회논문지
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• 제34권8B호
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• pp.812-821
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• 2009

본 논문은 다양한 멀티미디어 어플리케이션을 수행하는 hybrid NoC 시스템을 위한 새로운 동적 재구성 가능한 스위치를 제안한다. 기존의 고정된 스위치와 job 분배 알고리듬을 사용하는 hybrid NoC 구조는 효과적인 동작을 위하여 해당 NoC 시스템에서 수행될 어플리케이션을 정확히 예측해야 한다. 본 논문은 NoC 시스템에서 수행되는 다양한 멀티미디어 어플리케이션에 대하여 버퍼 오버플로우를 최소화할 수 있는 재구성 가능한 스위치 구조를 제안한다. 제안된 시스템의 검증을 위하여 임베디드 시스템에서 사용되는 다양한 멀티미디어 어플리케이션 중 MPEG4 동영상 재생, MP3재생, GPS 위치 계산, OFDM 복조를 대상으로 실험하였다. 버퍼 오버플로우는 단일구조의 서브 클러스터로 mesh 토폴로지와 star 토폴로지를 갖는 NoC와 비교하여 각각 평균 41.8%와 29.0%의 감소를 보인다. 전력 소모에서는 고정된 스위치를 사용한 hybrid NoC 구조와 비교하여 평균 2.3%의 증가를 보인다. 면적에서는 서브 클러스터의 구조에 따라 -0.6% ${\sim}$ 5.7% 의 증가를 보인다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.287-289
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• 2005

This paper presents a hybrid neural network system which used a Self-Organizing Map and Multilayer Perceptron for the problem of Malay syllables speech recognition. The novel idea in this system is the usage of a two-dimension Self-organizing feature map as a sequential mapping function which transform the phonetic similarities or acoustic vector sequences of the speech frame into trajectories in a square matrix where elements take on binary values. This property simplifies the classification task. An MLP is then used to classify the trajectories that each syllable in the vocabulary corresponds to. The system performance was evaluated for recognition of 15 Malay common syllables. The overall performance of the recognizer showed to be 91.8%.

• 제어로봇시스템학회논문지
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• 제12권11호
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• pp.1081-1087
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• 2006

Generally, biped walking is difficult to control because a biped robot is a nonlinear system with various uncertainties. In this paper, we propose a hybrid sliding-mode control method using a WNN uncertainty observer for stable walking of the 5-link biped robot with model uncertainties and the external disturbance. In our control system, the sliding mode control is used as main controller for the stable walking and a wavelet neural network(WNN) is used as an uncertainty observe. to estimate uncertainties of a biped robot model, and the error compensator is designed to compensate the reconstruction error of the WNN. The weights of WNN are trained by adaptation laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified through computer simulations.

• 한국광학회:학술대회논문집
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• 한국광학회 2006년도 동계학술발표회 논문집
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• pp.221-222
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• 2006

• 대한전기학회논문지:시스템및제어부문D
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• 제53권10호
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• 전기학회논문지
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• 제60권10호
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• pp.1832-1837
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• 2011

The fault current has increased due to the large power demand in power distribution system and network distribution system. To protect the power system effectively from the increased fault current, the superconducting fault current limiter (SFCL) has been notified. However, the conventional SFCL has some problems such as cost, operation, recovery, loss. To solve some problems, the hybrid superconducting fault current limiter using the fast switch was proposed. However, hybrid SFCL also has a problem that is protection coordination in power distribution system with hybrid SFCL. In this paper, the fault current limiting characteristics of hybrid SFCL with first half cycle non-limiting operation according to the fault angle, the resistance of superconducting element, and the magnitude of Current Limit Resistor (CLR) which are the components of hybrid SFCL were analyzed through the experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.882-885
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• 2003

In this paper, nonlinear echo cancellation using a correlation LMS (CLMS) algorithm is proposed to cancel the undesired nonlinear echo signals generated in the hybrid system of the telephone network. In the telephone network, the echo signals may result the degradation of the network performance. Furthermore, digital to analog converter (DAC) and analog to digital converter (ADC) may be the source of the nonlinear distortion in the hybrid system. The adaptive filtering technique based on the nonlinear Volterra filter has been the general technique to cancel such a nonlinear echo signals in the telephone network. But in the presence of the double-talk situation, the error signal for tap adaptations will be greatly larger, and the near-end signal can cause any fluctuation of tap coefficients, and they may diverge greatly. To solve a such problem, the correlation LMS (CLMS) algorithm can be applied as the nonlinear adaptive echo cancellation algorithm. The CLMS algorithm utilizes the fact that the far-end signal is not correlated with a near-end signal. Accordingly, the residual error for the tap adaptation is relatively small, when compared to that of the conventional normalized LMS algorithm. To demonstrate the performance of the proposed algorithm, the DAC of hybrid system of the telephone network is considered. The simulation results show that the proposed algorithm can cancel the nonlinear echo signals effectively and show robustness under the double-talk situations.